031: From PhD to Tech Leader: Unveiling Leadership Tactics in Big Tech

Ritendra Datta (00:00:00) - You are owning a bigger percentage of the company as your career grows. It increasingly becomes a gamble. You have to make intelligent guesses, so you have to do your own research about equity evaluation. Future potential of this company. As I was projecting future income at Databricks. I was like, I really believe in the mission of this company. I really believe that this company will do amazing.

Christopher Nelson (00:00:26) - Welcome to Tech Careers and Money Talk. I'm your host, Christopher Nelson. And today I want to answer one of the questions that's on many people's minds, which is where should we start our career? Do we start at an early stage startup where there's a lot of opportunity, or do we start at a mature public company where we can grow our skills and also get equity compensation? That's liquid right away. Today we're going to talk with a pretender who has grown his career working at Google and then Facebook, and now has taken his opportunity to trade time and talent at a pre IPO company, Databricks. I want to dig into the conversation to help understand what helped him successfully grow his career, from walking in as an intern to ultimately running teams of up to 200 people.

Christopher Nelson (00:01:18) - The second half of the conversation. I want to take advantage of the fact that he is an AI, artificial intelligence and machine learning expert to understand how this is going to impact the workplace of the future. I know there's a lot of noise in the marketplace out there. AI is taking people's jobs. AI is going to replace people. I want to get to the truth and understand what he really thinks from his vantage point. I'm excited for everybody here to meet the bartender today. Let's talk to him right now. 

Welcome to Tech and Money Talk. I'm excited to introduce everyone today to Ritendra Datta. He's the head of applied AI at Databricks. But that's not where he started. He started coming out of school with a PhD in computer science, and walked in the door of Google as an intern. Yes, you heard that PhD to intern nine years later left as a senior staff engineer to then go to Facebook to head up a or ultimately head up a 200 person team of reels and video recommendations. He has an amazing career story.

Christopher Nelson (00:02:24) - He's also the voice that can help us understand what is the future of AI in the workplace going forward. I'm excited to introduce everybody today to our data. Thanks for joining us.

Ritendra Datta (00:02:36) - Thank you so much, Christopher, for inviting me.

Christopher Nelson (00:02:38) - My pleasure. I mean, let's get right into it. I think that what sticks out in your story is you walk out, you've worked so hard to get a PhD, and then you walk in the door of Google as an intern. How did that feel?

Ritendra Datta (00:02:57) - Yeah. I mean, I think, like, you know, I was a poor graduate student. I was making, like, I don't know, like, just about enough money to save a couple hundred bucks every month after paying everything. So, like, first the big jump was money related, which is like, wow, that's a lot of money. In three months, I earned more than I used to earn as a grad student in a year, probably a year and a half.

Ritendra Datta (00:03:23) - And so financially, this was a huge deal. But more importantly, I suddenly got exposed to a different world altogether of talking to people, working with people that just deeply care about people and care less about research in and of itself. Publishable research specifically, because that used to be the culture that still is the culture in academia, where publishable research is the main focus, except in a very small number of places where publishable research is not absolutely front and center of how people are valued, like the MITs and Stanford's of the world have a little bit of a live in terms of, you know, what research goes on and how it's valued and whether it's published or not is less important, and it's more important to generate value through academic research. But that's not the case in most universities in the world. So I had a completely eye opening experience at Google where people didn't really care about publishable research. They cared about research, they were researching products. They were researching experiences and early days of Google, like 2008 Google, when I was an intern there, it was like literally the best place to work.

Ritendra Datta (00:04:38) - I could imagine a better place to work at that time. And I've been in the industry for a while, that was the best time.

Christopher Nelson (00:04:48) - And what and what were some of the things that made it that way? Like what were some of the parts of the culture that helped you really grow and flourish?

Ritendra Datta (00:04:58) - I think part of it was my personal transition very quickly from thinking about what I can do for myself to what I can do for others very quickly like that. I think I read this book and I keep referring to that book, Seven Habits of Highly Successful, Highly Successful People.

Christopher Nelson (00:05:19) - Yeah, that's right, Stephen Covey Covey.

Ritendra Datta (00:05:21) - This book is such a Bible for me. One of the habits is like, put yourself in other people's shoes. And as soon as I entered this, you know, internship immediately that happened to me. I'm like, hey, this is the first time in my life that I'm working on a piece of code that runs for a billion users.

Ritendra Datta (00:05:41) - Back in 2008, there were a billion, probably a billion users, a billion users using Google Search every day. And I was working on a search. So I was like, I made this change to this code. A billion people are affected by this. Like that. That was mind boggling, right? Yes. And when you do that, then everything else becomes pretty small. Like how much money I personally make, even how much money I was in the Google Pittsburgh office inside of the Carnegie Mellon University campus. So how much money Google Pittsburgh makes or CMU makes or, you know, whoever, like the smaller entities, suddenly becomes less important and the grand scheme of things suddenly emerges where the little changes I'm making are impacting people from around the world, 200 countries or whatever. And, you know, every day a little bit of my work is showing up there. You know, little, you know, mobile phones or at that time, like mobiles were not as big as like, right.

Ritendra Datta (00:06:34) - You know.

Christopher Nelson (00:06:35) - Yeah, PCs.

Ritendra Datta (00:06:36) - Desktops and laptops were. Yeah.

Christopher Nelson (00:06:40) - So. So you went to work growing your career at Google. You know, when did you start thinking that you were ready for management?

Ritendra Datta (00:06:50) - Yeah. So that happened, um, very organically. So Google has this concept of a tech lead, a tech lead. It's a much celebrated thing. Like if you all aspire to become tech leads, even though it's a very fuzzy concept. What is a tech lead? A tech leader, someone that is responsible for the team but not for the management part of like they build roadmaps for the team. Like what are you going to work on in the next quarter or next half or whatever, but not, you know, how are you doing individually? So there was this gap between like, what a tech lead did to what a manager did. And at some point in time, I found myself spending so much time with the people I was tech leading that it made sense to just become a manager and support their careers as well.

Ritendra Datta (00:07:38) - Like the main difference was I was already caring for their career, but I was not representing their career. I was not going into a, you know, a performance review session and talking about them. And I had to translate that to their official manager. And I realized that, like, you know, why not? Why not cut the middle person and just do it myself. And like, it was very organic. My managers thought that, you know, I was ready. He said, hey, why don't you manage? I had literally three people in my first team. It was just me and three others. And very honestly, I didn't do a great job as a manager when I first became a manager. But that's a separate story.

Christopher Nelson (00:08:18) - Yeah, well, I think it is difficult because it's interesting that you bring up that Google model because now outside, I've worked at companies outside of Google, never worked inside of Google. But as many companies study the management style, that is a concept that's used outside and this is how I explain it to people, if you first become a lead.

Christopher Nelson (00:08:39) - That can be a tech lead, that can also be a business lead where your job is to now divide up the work and deliver the results. But to your point, you don't worry about coaching and managing somebody through their career and all the things around that. And you also don't put money in their pocket or take it out. Those are things that you learn later. And arguably, while those can take less time, you know, as far as having the annual review or the quarterly review can, you know, there's less physical time in there, but that takes more skill and you have to be very adept at that. So I would argue, you know, and I'd be curious about your thoughts. But it takes time to make some mistakes, understand how to correct that, to really develop a management style that you, you can relate with and really works.

Ritendra Datta (00:09:29) - Yeah, yeah. The classic mistake I made was what you just said, like the classic mistake I made was micromanagement. It's like a horrible thing to do.

Ritendra Datta (00:09:39) - But you don't learn it till till it impacts you. So one of the things is that I'm starting with a failure story because it's always like the building block to further successes. That's right. I had one of the three people on my team after I got them promoted, and left my team because they were like, okay, you helped my career, but I'm not enjoying working with you. So that was a fascinating eye opening experience where I was like, this is the difference between a tech lead and a tech lead, like a tech lead manager there at Google, they called tech lead managers, which is like a manager of a small team, but someone who is very almost like an individual contributor, but with some management responsibilities. I was in that role and out of two out of three. When one person leaves, that's 33% of your team just gone. And I could not accept it. And I was completely shattered. But that really helped me understand that there's a huge difference between a tech lead and a manager.

Ritendra Datta (00:10:40) - Understanding the personal aspects of what inspires, what motivates someone to work was a new thing as I went into the manager role. So it was pretty interesting.

Christopher Nelson (00:10:55) - And so as you started growing, obviously you changed that and you said, I'm going to go correct that. Where did you start getting, you know, management training? And sometimes we get formal management training. Sometimes we find mentors, sometimes we find peers that are outside of our particular company. How did you start finding resources to grow yourself as a manager?

Ritendra Datta (00:11:20) - Yeah, I mean, all my life, again, this varies from person to person. All my life I have learned through observing others. I observe very keenly every single person, every single step. That's something I'm known for, for being extremely observant. So I often spend a lot of time watching other successful managers I watched. During these performance review sessions, I was paying very close attention to pairwise conversations, to what was resolving problems and what was making the problems worse.

Ritendra Datta (00:11:55) - Like observing my peers by peer managers was one of the best things to do. My manager was also. His name is Greg Freedman. He he at that time he was my manager, and I learned half of the empathetic management from him. Like he was incredibly empathetic toward everyone. He did not. He really understood where people came from. He was not super deeply technical, but he was super deeply involved in understanding people's psychologies and apply that every day to his management style. And it just was like the fact that someone can be that empathetic was eye opening essay. Say one more thing. One other thing. I learned this was probably right before I became a manager. Google used to have this training called the Edge Training. That was also like very eye opening from a learning to manage, learning to work with others. They have. I recently heard that they don't have that anymore, but it was one of those like three day experiences in some like place in California. Some like isolated place in California where you just you're hanging out with a bunch of colleagues at Google and you're doing team building exercises and you're giving each other very harsh feedback with with no prejudice, people you will not meet again.

Ritendra Datta (00:13:14) - And I actually didn't meet those people ever again. But we had this like 2 or 3 hour session where we would each give each other the harshest possible feedback around how we operated with each other during some team building exercises. And that was, again, such a small thing, so heartbreaking. Like I never was that day, I learned things about myself that I never, you know, observed. Because you don't always see yourself in the mirror. You don't always like to observe yourself in the third person. So like somebody who has no reason to tell me bad things about myself, I was somebody who has nothing to gain or lose telling me this like because all our lives we are surrounded by people who have incentives to say things in a certain way, who are that's that's primarily like you're related to them, you're working with them. They need something from you. You need something from them. Suddenly you are in this, you know, isolated place with a bunch of colleagues that you will never meet again. And they're telling you certain things.

Ritendra Datta (00:14:13) - I'm like, that is the most honest thing you can do. And you learn so much through that because you understand the connection between where people are coming from and what they're saying, the context behind the feedback. And that's also another thing I learned that, you know, context is so important when you give or get feedback, because if somebody has incentive to take your job and replace you with something, their feedback is probably not the best one to take. Actually, Mark Zuckerberg. When I was a marketer who is a pretty impressive CEO, like from within, one of the things he gets so much flak externally, but internally he's actually quite respected because he's very direct and honest. One thing that he always says he is extremely criticized, right. Like he's one of the most you know, he gets a lot of I mean, he has his follies. I personally have some concerns about that too. But one thing that he says, which is interesting, is. Hee hee.

Ritendra Datta (00:15:12) - The amount of negative press he gets. He personally says, I don't pay attention to all of them, but I pay attention to the ones where I know that they have my. They have good intentions. They want me to succeed. So that actually filters down feedback and you grow faster because of that.

Christopher Nelson (00:15:31) - Right? I think that is very insightful, is understanding the context and who's behind it and being able to filter out the stuff that is essentially noise. So as you're growing your career, at some point, you know, to get to Facebook where you're managing large teams of around 200, at some point you actually start managing managers and really start scaling your team. At what point in your career was that?

Ritendra Datta (00:15:58) - Um, I think. 20. I did the same thing my manager did to me, which is I turned my tech lives into tech lead managers at Google. So that was the first time, like, I think it's 2017, probably 6 or 7 years back. Um, it was very quick.

Ritendra Datta (00:16:17) - I actually like within a year or two, I started my team started growing so much that I needed more managers, and I think I found the perfect fit in certain people who wanted to manage, and I needed them. So it was mutual. And so I turned them into managers. And I think the process was very interesting because like, again, my personal experience of failure experiences, um, I saw in them and I gave them examples of how, how the, the consequences of doing that weren't great. And actually, I thought they sort of took that feedback and moved faster because I was much more careful about it because I was such a recent manager myself, I was able to like coach them through that recent transition, I think. So then my manager.

Christopher Nelson (00:17:05) - Yeah, well, I think that's really powerful is when all of a sudden when you're you have gone through some of those things recently and it's very real and visceral for you. You can turn around and I think provide that lesson very quickly to other people.

Christopher Nelson (00:17:20) - What was as you started scaling your team? You know, did you start getting further from, let's say, the technology and the coding on a day to day basis? And how did that feel? I know for myself, as my career grew and I started managing larger and larger teams, it became less about me hands on in the technology to really guiding, you know, larger impact through the teams. How did that work for you?

Ritendra Datta (00:17:48) - You know, like. If I love the technical aspects of my job so much, that was very hard to give up actually, for me and I. Even today, even in today's date, I am so technical that, you know, a lot of my reports tell me they are very surprised because they're not used to managers of large teams that are very technical, technical to the extent that I am never I'm never satisfied, especially the mathematical and statistical aspects of machine learning. And I am so interested in that. And I always find that's where I add value by fixing assumptions people make about, you know, the statistics and probability and the data science aspects, the deeper data science, the mathematical aspects of machine learning.

Ritendra Datta (00:18:34) - And I still continue to do that. One thing I've realized is that although I've been coding since I was eight years old, it wasn't very hard for me to give up coding on a daily basis. What was what is much harder for me and I still haven't given up, is when I see something wrong with the with a design, with software design, or in the case of AI and machine learning, the mathematics and statistics that are used to decide, you know, what is statistically significant, whether the change is meaningful or not, those kinds of things. I get really bothered when my team or my peers brush off, what do you call it? Like, you know, do away with the details because they are presenting to me. I was like, I'm not interested in the high level. I get the high level. I want to see whether you're doing the details right. And nine out of ten times I find flaws in flaws in those things. And so I continue to, even today, like yesterday, I had a meeting where I was writing the equation for how to evaluate some things at Databricks.

Ritendra Datta (00:19:36) - And I really enjoyed it and everyone was like, we didn't think of it that way. Okay. That's the value. Um, so I have always maintained a dual personality, one where I'm an empathetic leader because empathy is everything in that aspect. The other is as a technical design reviewer or as an architect. I wouldn't say architect. I would say reviewer of architectures, reviewer of designs. I've definitely switched from doing my work to reviewing other people's work a lot more, and I stay technical through reviews and through inputs in small ways, and draw the line for where I stop contributing and my team starts to take over because I know that, you know, I could keep going. But I think it's very tempting when you are into it. But I have learned the art of stopping at a point where it's no longer adding value. Right? Or it's not. It's starting to intrude into my a lot of people, a lot of actually like there's a sorry, I'm taking a long as a very good question, to be honest, is a fantastic question because like, I'm thinking about it all day, every day, and I've done so for years.

Ritendra Datta (00:20:52) - Um, one very specific thing that is relevant here is. What if I am too technical? What does it do for my team? How do they feel about that? Actually, a lot of people feel like it's a lack of freedom because if your manager is constantly technical, then they don't, you know, they don't get to be technical themselves. They feel like they have to always like to review with you. Like it creates a culture where again, the micromanagement creeps in.

Christopher Nelson (00:21:23) - Yeah.

Ritendra Datta (00:21:23) - So yeah. So then I have to spend like nine out of ten times I have to say, you know, I'm not going to go into the details because I trust you one out of ten times. I'm going to do that. I'm going to use that as a way to demonstrate how if you were in my place, how would you review your own work the remaining nine times? And so that's a good way to like, train, but also to maintain high standards because we have to balance all of these things we do.

Christopher Nelson (00:21:54) - And I, I think this conversation is so important because I do think and you mentioned before that your mentor slash manager, when you were at Google, he was not as much of a technical leader, right. And he may have been more of a business focused leader. And as we continue to grow our careers inside of technology companies, we can grow in different dimensions. We can be a technical leader that's an empathetic manager. We can be a business focused leader that understands technology. And I think more than anything, it's important to know ourselves, to lead yourself as you. Are you realizing I'm very technical? I could fall down this slope of micromanagement, but in reality, I want to now leverage that, turn that into a superpower that says we need to set standards. And you come from a very unique background having a PhD in computer science, loving that if you get a PhD in computer science, it's less about quoting and more about math. In some of those, those bigger ideas behind it.

Christopher Nelson (00:23:03) - But I, I think personally, that adds tremendous value to the team because then you're, you know, a coach in that direction. You're coaching them to raise their standards and managing yourself, saying, I'm not going to slip down into micromanagement and do that everywhere.

Ritendra Datta (00:23:21) - Yeah. You have completely liked it, I think that's exactly a great summary of what I was saying. Yeah.

Christopher Nelson (00:23:28) - Yeah. Well, I think about that too. And this is where as I talk with people today, coach, some people today, I try to let them know that understand what type of manager you are and if you're applying for positions or if you're looking for promotions, be able to describe that to your future manager or who you're interviewing with so they know what you're going to get. Because I also know there's different leaders out there that are looking for somebody, you know, Uber technical with a little bit of business or nowhere, actually want to be very business focused with a little bit of technical. That's all it's all out there.

Christopher Nelson (00:24:03) - You just have to know who you are. So as you start growing your career, the one thing we talk about here is, you know, equity, compensation. I'm curious about yourself, you know, coming from an academic background, you start getting a salary and you're like, okay, you know, this is amazing. I mean, I know for myself coming out of school, you start making the money and think, this is great. At the same time, there is this equity component that gives us so much more that pegs us to a completely different value as we're working in tech, especially larger tech. What was your journey to learn about equity, compensation and then knowing your value and what to ask for if you got promotions or or changed companies.

Ritendra Datta (00:24:47) - Yeah. Yeah, that's a great question because this was like we all understood money as graduate students. We were like cash basically. Yes.

Christopher Nelson (00:24:59) - Yeah.

Ritendra Datta (00:25:00) - Not money. Cash, right. Like, you know, you get cash like, oh, you have a bank account, you get a direct deposit every two weeks or whatever.

Ritendra Datta (00:25:07) - Yeah. And then suddenly there's this equity thing. It's so much more complex to reason about equity. There's suddenly like, there's a non-deterministic aspect to compensation where you have to make a decision all the time or every, every so, every so often you have to make a decision, should I sell this stock? And so first of all, like when I started out, equity was a very small portion of my compensation. As is typical, as you become a bigger and bigger part of a company, equity becomes a much bigger and bigger part of your compensation. This is not new information. Most people know this, but it also means that you start to own a part of a bigger and bigger part of the company. And so you are accountable for the success of the company in a way that you never felt earlier, because you're just getting your paycheck. Like, how does it matter? I'm a cog in a wheel, but the larger piece of equity changes your perception of your own company from feeling like you're a corner wheel to a much more big, stronger driver of the company's success, especially now that I have.

Ritendra Datta (00:26:13) - One thing you may have noticed is I've progressively worked at smaller and smaller companies like Facebook. When I joined, there were about 20,000 people. When I left it was 100,000. Now it's 180 or 190,000. It's crazy. Facebook, when I joined, was 30,000 when I left, and before that, the rounds of layoffs, it was 88,000 people. And then layoffs have brought it down to something. Something in the 60 thousands is still very big. Databricks is in the mid mid 10th like 5000-6000. I don't know the exact numbers in that range. Right. Much smaller companies like six 6 to 7000. I don't know exact numbers, but now suddenly you are a bigger player in a smaller company. So it has a very direct connection suddenly to like equity because you are owning a bigger percentage of the company as your career grows, a bigger percent of a smaller company. So even bigger relative to the size of the company. So the equity compensation, um, one thing I realized was that it increasingly becomes a gamble, but you have to make intelligent guesses about the success.

Ritendra Datta (00:27:24) - So you have to do your own research about equity, your evaluation, the future potential of this company. Like when I was deciding between the compensation at Databricks, for example, the obvious comparison point for me was, you know, first of all, how does it compare directly with my Facebook compensation? But also if I project to the future, what does the compensation look like if I believe in this company, if I believe in this vision? So that's something I did quite a bit as I was projecting future income at Databricks. I was like, I really believe in the mission of this company. I really believe that this company will do amazing things. When it got into AI before, I was big. Like, if you look at our CEO, who's pretty amazing if you hear his conversation from like 4 or 5 years back, he's saying he literally is saying this before anyone else. I mean, some people are, but he's particularly saying data and companies that do data and AI are going to win.

Ritendra Datta (00:28:27) - And, you know, four years down the line. Everyone is a bit like focusing on data and AI. Actually. That's right. He was ahead of everyone. So that's why I believe in his vision. And I believe that he can get it right with his, you know, predictions of the future. That's why I was like, I'm going to use that projection of the future of equity for a late stage startup to decide. And it made complete sense for me to move.

Christopher Nelson (00:28:56) - Yeah.

Christopher Nelson (00:28:56) - And some of the things you said there are so important that people think about when they are looking at companies to go to work for, and that you have to have your own thesis, you have to do your due diligence on the company. And this is one of the things that I advocate for is that you need to think like an investor. You're investing your time and talent, you could be continuing to remain at a company where if it's public, at least you're getting liquid, you're getting liquidity, you're getting additional capital coming in in the form of equity as compensation versus now you're going to pre pre-IPO company.

Christopher Nelson (00:29:34) - Obviously it's a unicorn. I think it could be traded today on a secondary market. So there could be some liquidity options. But you have to have a thesis. I also think that your career is similar to mine. And there is a pattern there that I've seen with a lot of other executives where they go to work for public companies first and understand what successful public companies look like. Then when you have that framework and you understand from a management perspective, from a operations perspective, setting standards perspective, then when you go and you start selecting companies to go to work for that are pre IPO, you're already going to have a filter that can filter out a lot of things that you don't want because you realize that doesn't have. And some of it can be very quantitative and some of it could be more qualitative, where it's like this doesn't have the feel of success. Something's not right here. Versus you looked at Databricks, you started seeing all the indicators that said, okay, this number one fits my thesis.

Christopher Nelson (00:30:41) - But you're also looking at the team members the way that they're communicating. I'm sure saying, okay, I can see being an owner in this company and us being successful with where we want to go.

Ritendra Datta (00:30:55) - Yeah, yeah. And it goes both ways, right. They're also investing in people like me who have worked at public companies and who have basically understood the success paradigms. And also they are also betting on how the equity packages are pretty strong at these levels. Right? So they're also using their precious limited equity abilities, like to, you know, compensate, you know, people like me who have worked at public companies because they want us to bring in some of the, like, the rigor that we see in more mature companies. So that's it. It works both ways. Yeah.

Christopher Nelson (00:31:34) - It does. And that to me is then that's your leverage. Your leverage is the more you can articulate your story, what you've delivered at Google, what you've delivered at Facebook, even some of the training and how you've been focused on this AI space, the length of time you've been there, that's all.

Christopher Nelson (00:31:52) - As you sit down at the negotiating table, that's all leverage that shows them. Here's the value that I can bring to the table, but it allows you to also ask for what you're worth.

Ritendra Datta (00:32:02) - Yeah, yeah. And I and I definitely mean, now I'm in the process of hiring people and I find it like at Databricks. And a lot of people actually do that. They actually when they have a conversation with me and they're trying to get a job, a lot of times they are actually pitching themselves in a way that I have not seen in the past. Like earlier, they were just like type in. They're like, oh, Databricks is an incredibly high bar company. So like, I've never seen a company of this high bar of technical talent for technical talent. I don't know about the other functions, like all the people who have done really well and I thought were amazing are getting, you know, rejections left and right. It's so then I think my point is that I, it's become very, very like, oh, it's not enough to write code like these candidates are now trying to sell themselves and saying, hey, here's what I can bring to the table.

Ritendra Datta (00:32:58) - And I think that's actually a winning strategy. When they do it tastefully, it shouldn't be cringe, but they should like, try to sell themselves to companies that are competitive and have more candidates, many, many more qualified candidates that they can hire. Then your differentiator becomes how do you sell to the company beyond just being able to show that you're technically strong?

Christopher Nelson (00:33:22) - Yeah.

Christopher Nelson (00:33:23) - And that's I guess what I'm hearing is, as I know when I was at Splunk and Splunk was post IPO and we were growing, we had a very similar scenario. And what I found with different people is a lot of people could walk in the door and tell you what they did, and they could say that, and that was very interesting, but they couldn't tell you so what? Meaning they could say, here's what I do, but they can't articulate the results that they delivered. And at a company like Databricks, that's what they're looking for, is not just somebody who has built the widget, but somebody who's built a widget, put that inside of the machine and understood the goals of the company to be able to align it to that.

Christopher Nelson (00:34:08) - And when they're looking for that, that extra bit that people can articulate, because that's what's going to make a good company owner, because that's what you're coming in as.

Ritendra Datta (00:34:18) - Yep, yep. Absolutely. Completely agree with that. Yeah.

Christopher Nelson (00:34:23) - And so going back to what you said before. You know, in that you start you're now working for smaller and smaller companies to get more and more equity. Was that a a strategy that you had been focused on, or was that something that's just happening organically?

Ritendra Datta (00:34:42) - I didn't have a very I'll be honest with you, I didn't I don't have a very ambitious money plan, to be really honest with you. I don't have a very organized way of thinking about how much money I want to make. I have some targets for, you know, you know, for the future. But it's not super. It's nothing like some of the other people I know. Someone who said they have. 12 different money managers that they work with. And you know how many money managers I work with? Zero.

Ritendra Datta (00:35:17) - I manage my own money. I do my own taxes. I'm far simpler in that sense. Right? Like I'm not very, I'm reasonably technical to be able to understand the tax code and we will file my taxes, even though with all the equity taxes, taxation, I mean, buying and selling homes has become a nightmare for taxation. But I did it. But at the same time, I didn't have a lot of clear strategy around things like, oh, here's what my trajectory will look like if I went to a pre-IPO company. Here's what it would look like if I continued my decision for careers that have been far more about what? I find it interesting, but I want to recommend that to everyone. I'm so passionate about technology, and I can go so deep that that's my that's the joy I get on a daily basis. Money is secondary to me in that sense, but it is also really important because, you know, it changes lifestyles. It allows you to retire early and all of that.

Ritendra Datta (00:36:10) - I understand that, but I have not personally not been. I'm not saying I'm very proud of this. I'm just saying that I'm not very organized when it comes to managing my money or creating a career strategy around money. My career strategy has always been around how my biggest thing is, which is a little bit different from all of these, is how is my day to day? And I learned this from one of my managers at Facebook. He used to always tell me, like, you should optimize for a few different things, and one of them has to be, how's your day to day? Would you take a pay cut to have a better day to day? And I always used to say yes. But effectively I have. By joining a pre-IPO company, I have taken a pay cut. Uh, not not not on paper. On paper. I haven't taken a pay cut. But in terms of cash that comes in on a weekly basis. I'm not getting those, like, you know, Facebook stocks that I used to get.

Ritendra Datta (00:37:06) - Right because and then sell that, sell them immediately and all of that, that strategy doesn't work. But my day to day is the main thing I use to determine my career path, to be really honest with you.

Christopher Nelson (00:37:17) - Yeah. Well, and that's okay. I mean, I think it's, people are looking for an opportunity to ultimately pursue their passions. Right. And some people feel that the corporate environment where you're, you know, getting a paycheck and ultimately working for somebody else can be too stifling. So they want to use it as a tool to get to somewhere else where they can pursue their passions. But ultimately, some people do love technology. You know, when you work in those companies, you get a front row seat to the future, and that's an exciting part to be every day. And then when you're working with a team that's excited and is highly technical in your building, great product. There's I mean, it's very similar to operating, I think, in other functions at a very high level of performance.

Christopher Nelson (00:38:11) - Right. You think about F1, formula one, you know, big technical winning things. I mean we win on the technical field as well.

Ritendra Datta (00:38:21) - Yeah. Yeah. And I'm glad you said that because one thing that's been common throughout my career is working on bleeding edge stuff. Everywhere I've been I like every time I've worked on something I have looked around like, who else is doing this? I'm like, no one is doing this thing that I am doing at this scale or this. No one is doing this, this thing. Period. So I've been very fortunate to have always worked in areas where I am just my day to day. It is good because of the work that I'm doing. And even if I ignore everything else about my career. But that's yeah. And one of the things I'll just add is that one of the things I have found to be a recipe for success, for people who want to make a lot of money, people who want to like your podcast team, right to, to to be successful.

Ritendra Datta (00:39:11) - I find that some of the people who make the most money are the ones who did not focus on money for at least some period of time in their career, where they were like. So they developed their skills and their abilities and their, you know, their passion to the extent where they became so employable in some sense that people were competing for their talent because they're like people talk about, you know, especially senior leaders. People talk about people all the time. How is this person, how should we get this person? Should we get that person? It will be amazing if you can hire that person, or this person will completely come in and change the way we work on things, that conversation. People need to have that conversation about you and that's when you start. Then you do the interview and then you're great, and then they're so desperate to have you. Then they have that leverage to like, ask for more money or whatever, like, you know, equity or whatever. And then, you know, they will oblige if you're that good, if they and if you're like moderate, then you suddenly hit a ceiling for how much you know, you know, you know, negotiation power you have it's true.

Christopher Nelson (00:40:18) - It's true. If you focus a part of your career on looking for the opportunities to deliver results, finding passionate people to work with that will help you build those deep skills. That's what I call your career capital, and that's going to give you leverage later on. And I think that the first part of your career, if you focus on building the career capital, you can then go on and leverage it. I didn't start working for significant equity till ten years into my career, because to your point, I was focused on how do I build skills, how do I do great work? And to your point, be on that, on that bleeding edge versus, uh, seeking the money. And then ultimately the money came because then you have that in the bag and then you can start making very interesting choices of where you want to work.

Ritendra Datta (00:41:10) - Yeah. And essentially what you're doing by doing what you just said is you're moving yourself to the extreme edge of the curve of like, like, like how rare is your skill set?

Christopher Nelson (00:41:21) - Right.

Ritendra Datta (00:41:21) - As you move more and more toward the radius, you're like the supply demand. You know, the standard microeconomic theory kicks in like supply and demand. And at some other time, there's not enough supply for the kind of skills you have. And so it very directly translates into how much money you can make. Because, you know, ultimately this is a market like, you know, employment is a market. It's a marketplace like any other. It is a marketplace. Yeah.

Christopher Nelson (00:41:47) - And the more rare and valuable you can be, the better you can have those conversations when it comes to compensation and equity.

Ritendra Datta (00:41:54) - Exactly, exactly. Yeah. Yeah.

Christopher Nelson (00:41:57) - All right. We're going to take a break right now. And we're going to come back afterwards. And we're going to dig into a couple of things. I want to dig into the double down strategy, and we'll talk a little bit about that for career growth. And then I want to pick your brain as somebody who is in the AI and ML space is as far as how that's going to change the workplace going forward.

Christopher Nelson (00:42:19) - We'll be right back. All right. And we are back here with the second half with Tendra data. And tendra thinks about career in a way that I think is refreshing. I think it's important for us to listen to what he has to say. And he wrote a very interesting medium article on the double down strategy that I think has enough quantitative information and qualitative information that helps us think about promotions in a completely different way. Can you give us a high level of the double down strategy?

Ritendra Datta (00:42:55) - Yes. So I think like it's, it's the very simple idea that and that's a, there's a very specific thing around um. Career growth and doubling down in that article. But at a high level, this is about taking much more ownership of your career. And there are many, many such strategies which can accelerate your career. This specific one was more on the mindset of growth because like nine out of ten times, um, like people don't really like to think about beyond their next. Like when they think about promotions, they think about their.

Ritendra Datta (00:43:44) - Next promotion only because that's how we've always been taught to think. But the problem with that is like, I have a graph in that article, but it's basically the idea that your skill sets need a longer time to build skills for the next promotion. If you don't start now and you start your clock starts as soon as you are ready. Your clock doesn't start after you get your next promotion. So if your next skill set requires two years or let's say three years, and your next promotion is one year down the line. So using one strategy where you don't focus at all on your next promotion or promotion is a more specific way of representing a career jump in some, some sense. Right. There's a broader sense of this that's not very specific to the, the, the notion of, you know, you get to level N plus one, which is, which is a specific invention of corporate America. The more general concept here is like, you do bigger and greater things.

Ritendra Datta (00:44:50) - And in order to do bigger and greater things, you need to, like, have developed new skill sets that you didn't have in your previous level. Right. So yeah. Good.

Christopher Nelson (00:44:59) - I know I was going to say, let's go back to the example that we had earlier. I think it's very salient. So we talked about team lead and then team lead manager. And we talked about getting a team lead. You're really managing work. You're saying I'm going to get a big piece of work. I'm going to carve it up. I'm going to give it to the team as a lead. And then I'm going to focus on that result coming back, and I'm going to roll that up to my manager. I'm not managing their career. I'm not mentoring them on sort of how they do or team interactions. And I'm not putting money in and out of their pocket now. That's if I'm in one. I'm thinking, okay, how do I get to be a team lead? You're working on this, the work breakdown structure and getting it back.

Christopher Nelson (00:45:44) - However, if you're thinking, uh, you know, doubling down and you're thinking beyond that, you're going to think the newest person who comes in on the team let me work on some of my mentorship skills. And I heard you say this when you became the team lead, you all of a sudden started working on mentorship and doing other things that prepared you for the team lead manager and that that is really the double down strategy where you you're looking at the next role and saying, what's the skill I need to stack on? If I start stacking that on when I get my first promotion, I'm now getting that runway of developing that skill, hardening it. And what I like about this double down strategy is that it actually creates much more sustainable careers, because we have to stack these skills, right? The skills that you have now have been stacked over years and years from where you were when you walked in the door at the intern. And if you just tried to be on board with the skills you have today, it wouldn't happen.

Christopher Nelson (00:46:51) - Because you definitely need time. You need to have experiences. You need to have successes. You need to have failures. So the sooner we can look towards our career and understand what we want and start adopting that now, that will allow us to, I think, grow our career more sustainably. That's what I thought was the interesting part of your thesis.

Ritendra Datta (00:47:13) - Yeah, yeah, I think there's a broader version of exactly that. That example was super classic. Like, you know, these are not technically promotions. You know, I see individual contributors to tech lead to tech lead manager. While a while as an I see if you behave like both a tech and a tech lead manager without having those titles, you'll both of those will come to you sooner than you think. If you start to think about management only after you become a tech lead, then you've already lost a bunch of time. But what if from day one, no one will call you a manager from day one? But what if you behave like one? Then they'll see that in you.

Ritendra Datta (00:47:53) - And that's the strategy in action, where everyone starts to think of you as a natural manager for that team. And so that just works out similarly. Like, you know, when you do this double down strategy at a much bigger scale. Again, I learned this from one of my managers. Like when you're running a 10% company or sorry, an organization, most people will think, okay, how do I scale this to 100 people? But my manager said, how do you scale this to 1000 people? Like from 10 to 1000? Seems like a huge jump, but it's really, you know, it's all in your head how limited you want to be. Like, you can still go and observe those VP's that are running thousands or senior vice presidents that are running 1000 plus people, or what do they do? How do they scale? You can start to observe them like nothing prevents you from thinking really big, but not necessarily immediately getting there. So like so that's overlapping my graph.

Ritendra Datta (00:48:49) - The timeline overlaps where you're building all sorts of skills at the same time. You're not going to get those. Promotions or know not going to get to 1,000% right away. But you're ahead of everyone in your peer group who are not doing that because you started training for it. Yeah, for everyone else.

Christopher Nelson (00:49:08) - You started getting repetitions. What are some of the common mistakes that you're seeing? Early stage engineers or early stage engineering managers making that are really avoidable?

Ritendra Datta (00:49:21) - Not paying attention to communication skills. Written, verbal. I think a lot of people in tech in America are not native English speakers, but they just instead of trying to figure something out, do something about it, they just like to focus on the things they are good at. Like we all tend to focus on what we are good at. Like that's a very common thing for a human. It's human nature for us to do the things we are good at because we get more and more appreciation. We get addicted to that feedback loop of like getting more appreciation for what you're already good at and not venture into things that you're not good at because, you know, it's it's it is a it's a painful process to like, you know, expose yourself to something that you're not good at and then having a period where you're not appreciated for this.

Christopher Nelson (00:50:11) - Yes. Right. So that's right I think so.

Ritendra Datta (00:50:14) - But then like, what if you started with written communication, which is much easier to pick up and then just got really good at it so that, you know, you don't speak much, but everything you write about your technical work is immediately passable by everyone. And people start looking up to you. So that's number one. Number two is being very for especially for managers. This is a huge mistake which is focusing too inward. What does my team get to do? What is my scope? What is it like? How do I benefit from this? A lot of managers make the mistake of exposing their personal desires a little too quickly because, I mean, we all aspire to grow like there's no there's no secret. Like we are humans. Everyone gets it right. But when you're blatantly doing things that make you look selfish, oh, I want this for my team. I want this scope, I want that. I think it really makes people think this person is going to grow up to be a politician, and they're going to, like, continue to fight for scope and not sometimes they would do that at the expense of the company's well-being.

Ritendra Datta (00:51:19) - So ultimately, like, you know, for especially for technical leaders and managers to come across as being company focused, putting company before yourself and your even your team, um, then suddenly, like, if you're able to project that, then people see people trust you with more and more because they don't see you as too strongly tied to the little world that you live in. Right? So again, to repeat, like for especially for ISIS, but also obviously important for managers, um, be a great communicator in whatever form of communication that is universally passable. It doesn't have to be verbal. It can be written, it can be, you know, um, you know, I don't know, maybe there are other ways to do it, but typically it's between verbal and written. Um, and then the second one is about not being too selfish and inwardly focused, especially when you communicate with your leadership team, especially when communicating with your peers. You want to come across as I want to do the right thing for the company.

Ritendra Datta (00:52:24) - That's right. And I think you want to believe that. Like, again, this really ties back to the earlier thing you said about equity compensation. Like as you start to as you start to get more and more, as your compensation starts to get more and more tied to the equity of your company, you ought to start to think in terms of the company, because your finance is not tied to your personal team's contributions alone. It starts to get more and more tied to the whole company's success. So you ought to think in terms of, you know, if you're if there's a competition going on between you and some other teams for some scope for some. This is, by the way, this is happening in every company.

Christopher Nelson (00:52:59) - Oh yes, yes.

Ritendra Datta (00:53:00) - Everyone wants a seat at the table when it, when it's, when it concerns the eye. And this internal fight is going on around these things in every company in the whole world. I don't end there because I think that I can get that.

Ritendra Datta (00:53:15) - That's a different conversation. But my point is about not being selfish.

Christopher Nelson (00:53:18) - Not being selfish. Yeah. And I think, you know, communication is so important because nobody's going to tell your story for you. And I'm sure you've seen this too. And this also goes to career growth as well. If. If you believe that you're going to get to a director, a manager, a head of a function, and you don't have to tell stories and you don't have to communicate succinctly, you're wrong. Because storytelling communication becomes so important because we're communicating up all the time, justifying budget, you know, discussing why things are delayed or if we need things from other teams, we need to be able to articulate that clearly. And so communication is absolutely critical. And then thinking like an owner of the company and focusing most on. What is the company focused on? The customer? If so, then we all need to be aligning to what the company wants, because that's ultimately going to allow this asset to grow in value.

Christopher Nelson (00:54:22) - That benefits us arguably more than the paycheck.

Ritendra Datta (00:54:26) - Yeah, yeah. And I'll just say one thing. Exactly what you said. You summarized it well. I think ultimately we are all serving ourselves and our close loved ones and whatnot. So it just changes the time horizon, right? Like basically like if you're fighting for the company, ultimately you're still serving yourself. It's not altruistic in any way. You are just making a better financial decision for the long term for you and your family in some sense by focusing on the company. So it's like it's somewhat myopic to think that, you know, you'll make a little bit more money, get that next promotion or whatever. But what if you just really cared about the company, then you suddenly your company is so much more successful that the leverage is much higher with.

Christopher Nelson (00:55:08) - That, right?

Christopher Nelson (00:55:11) - So I do want to take the conversation towards the direction of AI and this, you know, very powerful tool set that's entering companies and engineering and engineering teams right now.

Christopher Nelson (00:55:24) - You know what? You know. What are you seeing? How are you seeing this play out? You know, not just Databricks, but I'm sure that you have your ear to the ground in other companies as well. How do you see this benefiting teams? What do you see? Some of the risks.

Ritendra Datta (00:55:39) - So first of all, like I have seen in companies for, for. 14 years now, right? Yeah. So it's just gone mainstream more recently, thanks to OpenAI and chat. GPT is, you know, phenomenal growth and basically like it became a household thing because, you know, the generative AI in particular. I mean, in my world, I have two kinds of AI, right? Like supervised. I mean, there are multiple. There's a smaller group of other kinds, but like, yeah, but the big ones are supervised learning, which is machine learning. That is basically saying, if I can, if I give you this data point, can you tell me which category or what number it maps to? Right.

Ritendra Datta (00:56:24) - That's the basic, overly simplistic version of supervised AI. And then there is generative AI various giving a prompt. And you're getting a lot of content back, like it's no longer just saying yes or no, 0 or 1.5. It's actually giving you. So I think it's called the generative portion of AI that has caught the fascination of people because that's the AI we grew up watching on in Hollywood. Like supervised AI is super important but boring. Like, oh, can you tell if this is a cat picture of a cat or a dog? Like, how do you even like it? It's important because every single day a Google search is powered by thousands of such, you know, classification decisions, right? Or like if you're using Gmail, you know, the spam filtering is one of the most powerful pieces that improves your life on a daily basis. But no one talks about it, right? Like spam filtering it is leaps and bounds ahead of the Yahoo mail or Hotmail days where, you know, we were full of spam and like, only you know, you had to really filter, like you're literally wasting some chunk of your time every day sifting through a bunch of email.

Ritendra Datta (00:57:31) - Now, these newer email clients are just like classifying all the emails into categories. And you just it really helps you focus on what's important, saving you a ton of time. But no one talks about that. That's like the kind of AI that I grew up on. But then I also was working in generative AI for discrimination. It's a different topic, like generative AI was also being used when I was in grad school. I actually built generative models like 14 years, 15 years back. Not for the purpose of generating text, but for explaining things, because there's this idea that if you generate something, then you have the best vision view of the world, and then using that generated generation, then you can tell the difference. Then you can do supervised classification in any way, that's a separate topic. Coming back to your question about how I'm seeing this play out, I'm not an expert to talk about the whole industry and how everyone is doing it. From my personal viewpoint, I'm seeing a lot of noise in this space that is like people are very worried about what is going to happen if they don't jump on the bandwagon, but they don't know what it is.

Ritendra Datta (00:58:46) - They're somewhat clueless, like there's not enough experts out there to explain to them which part of this AI boom is valuable. The funny thing is, everyone wants to do generative AI, but a lot of companies haven't even gone through the process of doing supervised classification of the things that would make their daily lives immediately better. They go straight to generative AI because of ChatGPT. And they. I hope eventually this thing rationalizes to the point where the broader umbrella of AI itself becomes a much used technology in every single company. Some of it is generative, some of it, some of it is discriminative, which means that in some, some AI is just deciding to do this. Do you do that? That's just super useful. And then you also use generative AI to write your presentations, improve your company's documentation. You're writing those documentations using a lot of context from within your company. And the other thing that I think generally companies don't realize is how much data they're sitting on. Each company is sitting on a goldmine of data that they're they could use for both discrimination and generation of content, which I think I think when consultants start to become knowledgeable consultants start to talk to these companies, they're going to start to tell them, hey, I'm so glad you're paying attention to I thank you for for paying attention to this that you ignored for a decade.

Christopher Nelson (01:00:15) - Yes.

Ritendra Datta (01:00:16) - By the way, by the way, do the simple thing first and then go into this more complex thing. And I think it will start to like, play out in a very meaningful way where everyone is going to benefit from AI. But the catalyst was something, but the outcome was something else. I think that's how it's going to play out for the next five years. And then eventually I don't really. I have not really thought deeply about how this is going to evolve over a very long time horizon. Right. But over the next. 3 to 5 years. The attention is basically like Apple released the iPhone. Everyone started building mobile mobile phone based applications, but they also started building for Android. They started building for BlackBerry. They started like this. The catalyst was one thing, but it impacted the broader ecosystem is how I see it well.

Christopher Nelson (01:01:05) - And I think you're bringing to life some of this stuff that I've been hearing from other people, too. And I think it's important to, you know, have somebody with your experience talk about this if we're in that phase where I call this more of the excitement and wonder phase and that can, you know, turn to a little concern and worry.

Christopher Nelson (01:01:23) - The reality is, you know, we're just especially in the generative AI side, just trying to understand the value that it can bring to the table. And this technology needs to mature. It needs some time to harden and mature over the next couple of years to really become useful.

Ritendra Datta (01:01:42) - Yep, yep. Exactly. And I think it will happen. I think it's just a matter of time. And like I think again, there will be a cascading set of companies on their timelines of when they get there. Mature companies like Google in particular, like Google built all of this before everyone else at scale. They were very careful about releasing all these things because, you know, they're always under scrutiny. They don't want to mess things up. So but, you know, compare that to some traditional banks for example. Right. Their time horizon starts now.

Christopher Nelson (01:02:17) - Right. Yeah. And you know, they're going to.

Ritendra Datta (01:02:19) - They're just going to have to accelerate to the point where they are competitive with the more technical banks that they are competing with, right.

Christopher Nelson (01:02:26) - Okay. So that's a good point to tease out. The companies that haven't been incorporating this into their tech stack are going to need to start exploring and figuring out what are the one, two, three steps they need to be taking now. Because in 4 or 5 years, the companies that have been working on it are going to now be at a completely different level of maturity.

Ritendra Datta (01:02:49) - Yeah. And I think a classic example I think of is Capital One versus like a lot of these smaller credit unions like or I. I'm sure there are other banks also like that are not very technical. And like Capital One was technical before all of these other companies. They had AI teams and data science teams before all these other companies, I think. So I'm not an expert at this, but what I know is that Capital One was ahead in that banking space from a technological perspective. And the other companies, if they want to compete, they have to catch up very quickly. And they have to have to do that in an accelerated timeline because otherwise, like, you know, the gap will just keep increasing or stay constant.

Ritendra Datta (01:03:31) - They have to bridge the gap. Right.

Christopher Nelson (01:03:33) - And yeah. And try to accelerate its closure. Interesting. So then do you see. Any immediate impacts, or I'd say like in the next 12 to 24 months and just in the general workspace, you know, in tech around generative AI.

Ritendra Datta (01:03:52) - Yeah, I think the way people are talking about this is again. I wouldn't call myself an expert, but I agree with this vision, which is that. I am not going to take people's jobs. But people who are used. Employees who are. Getting the assistance, maximizing the assistance from generative AI are going to outperform those that are not doing that. It's a very safe thing to say because it's less controversial, like AI is taking our jobs, but like all it says is. Everyone should start to use AI in their world, right? However they work to incorporate that into their, you know, process so that everything they do is just better. And when everyone else is doing that, you start to like your actual progress slows down.

Ritendra Datta (01:04:52) - Imagine the difference between writing, let's say, your task with your tech writer for a company or task, with writing a documentation for a new feature your company is building. Like that's your job now. Between two such people. The person that starts out with a draft from some kind of large language model, like llama or OpenAI or Mistral or Mosaics models. You end up with a reasonable first draft and then iterating, tweaking it, getting the facts right, removing hallucinations and all of that is ten x faster. Similarly with code programmers, if you start with a draft of something, you describe something you want to solve, and you know these lines generate some code for you, and then you realize, oh, there's a bug here, and this is this, this, this is not exactly right. Again, ten x. So people are generating content, generating code. All of them need to start using generative AI immediately. Otherwise they're immediately going to their counterparts are going to get a, you know, get a head start.

Ritendra Datta (01:06:05) - And so but you know, unfortunately, what I think it also means is that there will be fewer jobs down the line in the creative space because I this is my guess is like if if you could do everything, if you do everything ten x faster. But the need. The demand is not ten more. So something's got to give, right? Like if everyone's ten more productive, but the need is only two x more, then there's a gap that's created.

Christopher Nelson (01:06:38) - Right? There's essentially you have more productive people that are out there that are able to fill more of the gap versus those that don't. And you know, what I'm hearing very clearly is it's important for all of us to start learning and adopting to, you know, generative AI right now to essentially stay ahead of the curve. Right. No, don't get behind the gap.

Christopher Nelson (01:07:01) - Yeah.

Ritendra Datta (01:07:02) - And I have a very specific example that I'm heartbroken basically because I have lots of recruiter friends, people in tech recruiting, a lot of them have lost jobs recently.

Ritendra Datta (01:07:11) - It's just heartbreaking to see this, like so many, so much of that that's not generative AI, but that's like AI, broader AI of like just sifting through resumes, filtering them down like those. A lot of these jobs are sort of getting replaced by some kind of agent that is doing this at scale. And companies are okay with missing out on some good candidates because they're sifting through them, they're getting a few good ones. They're missing out on a few good ones, but they tolerate that the saving that they make out of swapping humans for, you know, AI based sourcing is so much more compelling that they just don't need that many sources. They don't need that recruiters and every single company I know of has had some kind of recruiting layoff or, you know, people, people operations, layoffs of some kind, which is pretty heartbreaking. But you know, like it also means that certain categories of jobs are just going to be less needed, like the supply demand curve across the spectrum of different types of jobs is going to shift.

Christopher Nelson (01:08:19) - Right.

Ritendra Datta (01:08:19) - Because of yeah, that's I think that's the most meta thing I can say about the question that you which is, you know, I give some specific examples, but I think what you're saying there's going to be a shift in distribution.

Christopher Nelson (01:08:29) - Between.

Ritendra Datta (01:08:30) - Supply and demand.

Christopher Nelson (01:08:31) - Yeah, there's going to be a shift in distribution. And the more that you can adopt this new technology and understand where you can build skills and where you can play a role, I think it's important because, you know, more than anything, we, you know, working in technology, we have to constantly stay ahead of it, stay current to try to get ahead so that we can understand where the where the opportunity is.

Christopher Nelson (01:08:56) - Yep, yep.

Christopher Nelson (01:08:59) - Well, thank you for that. Before we go, we usually wrap up with a fire round. So I'm going to ask you five questions right now. Just some crisp succinct answers and we'll get out of here okay. So what is the worst career advice you've ever received?

Ritendra Datta (01:09:18) - Fight for your scope.

Christopher Nelson (01:09:22) - Fight for.

Christopher Nelson (01:09:23) - Your scope. That goes against what you said earlier. Number two, how do you keep learning?

Ritendra Datta (01:09:30) - Just keep your eyes and ears open. Everywhere you go. Treat every moment of your life as a learning opportunity. Because everything, everything you learn is transferable.

Christopher Nelson (01:09:46) - That's huge. What do you do to recharge your batteries?

Ritendra Datta (01:09:51) - I am a filmmaker and a theater director and screenwriter. I get huge amounts of relaxation from storytelling and just watching great movies as well, because that's where I also get ideas. So that's a really nice feedback loop.

Christopher Nelson (01:10:08) - Oh that's great. What's the advice you give your younger self in tech?

Ritendra Datta (01:10:16) - Don't obsess over details. Get the big picture right as soon as possible and use a top down strategy. Even the most detailed little things that you do, because it's very easy to lose, you know, the reference frame of what you're doing within the grand scheme of things. And that's something that changes the way you do everything.

Christopher Nelson (01:10:44) - And finally, what soft skill has helped your career the most?

Ritendra Datta (01:10:50) - Storytelling and communication, because that's something that I've also said earlier, is that changes the way people perceive you, whether it's good, it's fair or not, I don't know, but it does change people's perception, like people who speak more succinctly, even when the overhear that from someone else who did all the work.

Ritendra Datta (01:11:11) - People then go to that person in the future instead of the person who did the work. It's an unfair advantage to be good at communication, but it really is.

Christopher Nelson (01:11:20) - And I think more and more people need to understand that. Well written draw. I can't thank you enough for your time. I've taken a lot away from this and I know everybody else has too. I appreciate you so much. Thank you.

Ritendra Datta (01:11:33) - Thank you. Thank you so much for having me. It was such a fascinating conversation. A lot of questions required me to think a lot, rethink a lot of things. Thoughts I had earlier.

Christopher Nelson (01:11:42) - Yeah.

Christopher Nelson (01:11:42) - Well appreciate it. All right. Thank you. Thank you so much for joining me in this conversation today with Tendra. I hope you got a ton of value from it. I do want to ask you one thing. If you want more insights around career and what's happening in the job market, what are the skills that you need to learn? Also, what are some key fundamental skills that we need to build as we're growing our wealth? I would ask that you subscribe to Tech Career and Money News.

Christopher Nelson (01:12:09) - That's right, TechCareersandMoneyNews.com is our latest offering, which is a publication that comes out weekly that gives you a lot of insights around career money and what is happening when it comes to equity compensation and the companies that you want to work for. Please subscribe now.