AI | Podcast | Culture | Media&publishing
Shobana Radhakrishnan on Leadership and Consumer-Centric Experiences
April 8, 2025 25 min read
For Shobana Radhakrishnan, engineering leadership isn’t about control — it’s about cultivating passion, purpose and products that delight users. As the Senior Director of Engineering at Google TV, she’s helping shape the future of AI-powered entertainment by empowering teams, removing friction for users and championing a culture of continuous learning.
On this episode of Keep Moving Forward, Shobana shares how embracing curiosity, hiring for motivation over resume lines and staying close to the user experience can transform both products and people.
Building a Career Around Curiosity and Impact
Shobana’s love for engineering began early while fixing things around the house with her father. At the time, it just felt like fun. But that early experience planted a mindset: building things is joyful, and trying new things shouldn’t be scary.
That spirit has carried her through roles at startups, mid-sized companies and now one of the world’s largest tech organizations. She’s worked across the full tech stack — from low-level systems to the cloud to AI personalization — always guided by a simple question: Am I having fun, and am I making an impact?
This same philosophy shapes how she builds teams. Her leadership mantra — “hire the best, inspire them and get out of their way” — is rooted in hiring not just for technical expertise, but for what she calls “DNA.”
“DNA is what makes someone tick,” she explains. “Are they energized by automation? Do they wake up thinking about user experience?” Hiring for this deeper motivation, she believes, leads to teams that naturally push boundaries and don’t require micromanagement.
Once great people are in place, Shobana shifts her focus to creating an environment where they can thrive — by removing blockers, aligning them with meaningful goals and fostering a culture of ownership and trust.
Leading With Empathy — and Staying Close to the Work
Shobana balances team autonomy with organizational alignment by clearly communicating the long-term vision — what she calls “point B” — while giving teams the flexibility to chart their own course to get there.
She maintains close feedback loops through roundtables, office hours and surveys. These touchpoints not only surface ideas from all levels of the organization, but also help her stay attuned to team dynamics and culture. “Great ideas don’t follow titles,” she says. “They come from anywhere.”
At Google TV, she’s solving a familiar challenge: helping users find something great to watch without wasting time scrolling. Her team is using AI to reduce that friction — leveraging large language models to summarize user sentiment about shows, personalize recommendations and explain why a piece of content is being suggested.
But personalization at this scale comes with responsibility. “TVs are shared devices — families and kids are watching together,” she says. That means privacy, accuracy and family-friendliness are built into the system from the start.
Embracing Learning and Looking Ahead
Continuous learning is a non-negotiable part of Shobana’s leadership style. She carves out time to read academic papers, participate in customer calls and learn from postmortems — modeling the behavior she wants to see across her teams. “Every meeting is a chance to learn,” she says.
That learning also shapes how she thinks about the future. Shobana believes we’re just beginning to understand how AI will transform entertainment. From real-time dubbing to hyper-personalized experiences across devices, the opportunity is massive — not just for efficiency, but for inclusion.
“What used to take months — like making content globally accessible — could soon take minutes,” she says. For Shobana, the promise of AI isn’t just about personalization. It’s about democratization. “Anyone connected to the internet should have the same opportunity to learn, create and grow. That’s the real promise of AI.”
Transcript
Shobana Radhakrishnan:
I think AI is going to fundamentally change the way we do entertainment in many ways, and many ways that we have not even foreseen yet. We are just getting started and scratching the surface, is what I strongly believe.
So, there is drastic productivity improvement, I think that will happen in the entire entertainment industry. And then we also usher in, I feel, an era of more inclusive, more globalized content because accessibility which may take months, and many corporations may not even be able to effectively prioritize accessibility and global inclusion, this could become a reality in just minutes where everyone builds global products, and the local audience is just as enamored as the audience in your primary markets.
Caleb Brown:
Hey, everyone and welcome to Keep Moving Forward, the podcast from X-Team for tech professionals who are passionate about growth, leadership, and innovation. I'm your host, Caleb Brown, and in each episode we'll dive into candid conversations with the tech industry's brightest minds, seasoned leaders, forward-thinking engineers and visionary experts.
Today, I'm thrilled to welcome Shobana Radhakrishnan, Senior Director of Engineering at Google TV. Shobana's journey spans startups, mid-sized companies and tech giants, giving her a unique perspective on building and leading high-impact teams across different scales. Her leadership philosophy centers on hiring the best, inspiring them, and then getting out of their way. This is an approach that has helped her drive innovation and create user-centric experiences.
In this episode, we explore how Shobana and her team are transforming the television experience through AI personalization and seamless cross-device integration. She also shares insights on balancing autonomy with alignment, fostering continuous learning, and building consumer-centric engineering teams that thrive on innovation.
If you're interested in the intersection of leadership, AI-driven entertainment and creating products that truly delight users, this conversation is packed with valuable insights. Let's dive in. Shobana, thank you so much and welcome to the show.
Shobana Radhakrishnan:
Thank you, Caleb for your kind works of introduction. Super excited to be here. Love your show.
Caleb Brown:
Awesome. Very happy to hear that. And so let's go ahead and just jump in with that personal and professional journey.
So, your engineering journey started quite early with your father's influence. Can you tell us a little bit about how those early experiences sort of shaped your approach to technology and problem-solving?
Shobana Radhakrishnan:
Absolutely. The example that you just mentioned where I helped my father as a 10-year-old, 11-year-old child with fixing things around the home. When I was experiencing them, I didn't even realize I was into engineering. It's when several years later, more than a decade later when someone asked me, "So when did you first get interested in engineering?" it made me think, because I had never been asked that question before.
And as I reflected, I realized maybe that was my first exposure to engineering. Even though all I thought was I was hanging out with my dad and doing stuff around the home, I feel like a couple of things that that, I think made me implicitly record, because when you're 10, you're not really thinking about a career, at least I wasn't, is A, building and fixing things is easy. And B, building and fixing things is fun.
And I think once you start realizing that, then whatever career you pursue, you're always going to carry that fundamental thought with you for decades and decades. And irrespective of, you mentioned the several places I have worked in. So I went into a engineering college. I moved to the U.S. from conservative southern Indian family to pursue my higher education here at the UIUC in computer science. And then I made a lot of shifts from medium-sized companies to large companies to startups and now back to a huge-sized company.
And I feel like that has always driven my choice of, "Does this feel like I'm going to have fun?" It's almost like following your passion and just getting a sense of, "Does the team have people that I'm going to have fun hanging out with and working on this?" I feel like that's what was true when I worked with my dad on those little things around the home. And it is still true of how I gravitate towards a job or decide what to pursue. Whether it was education or a job, these have been my driving factors.
So I think these early experiences that you form, and just not having any fear of trying to do things that you're not familiar with.
Caleb Brown:
Awesome, and that makes sense. You've worked across very different scales of companies, as you've mentioned, from startups to, of course tech giants. What motivated those transitions, is one question I have. And then I'm also interested in how that diverse experience influenced your leadership style now?
Shobana Radhakrishnan:
I feel very lucky to have worked in very different areas of technology and also very different kinds of companies and cultures because I think what I am now, or how I look at organizational culture has been almost intentionally by, for instance, been shaped up by all these experiences.
And also, I've been blessed to have worked in all parts of the tech stack, really working on device drivers very close to the hardware layer, all the way to servers, to the UI, to the cloud, and now working on bringing the goodness of LLM to Google TV. So I feel I've been fortunate along that direction as well.
To your first question of what motivated these changes, I feel like it is always a couple of factors. I always look for, what are the moving-towards factors versus the moving-away-from factors? So my transitions have been a mix of people reaching out or me deciding to pursue a different career.
So when I feel like I am bored or I'm not being as impactful because there's not a lot of change to be influenced, things are stable, then I have thought about, "So what can I do that's even more exciting?" And usually it's possible to figure that out in your current role and company, and sometimes it's not. And I've usually worked with my team to say, "Hey, I have this unsatisfied passion and I'm looking to do something different." So I've been typically, very transparent when I have that.
But more of it has been people either reaching out or some opportunity being presented and then me feeling like, "Oh, maybe I'll talk to this team." And usually that has happened because the opportunity is going to stretch me outside my comfort zone.
Caleb Brown:
What was your vision when joining Google TV and how has that kind of evolved as you've helped transform, sort of a more traditional TV experience into what Google TV is?
Shobana Radhakrishnan:
So the idea asking this question, because Google TV has been one of the most exciting career decisions I have made because first of all, what we were trying to solve for resonated for me as a user. And that's magical because at Google TV, what we are trying to solve is what I call this Friday evening moment where after a long work week or a school week for kids, you're going home. You just want to kick your feet up on your couch and just find something relaxing or fun to watch. And then you end up spending 15, 20 minutes or even longer just looking for something to watch. And oftentimes, you click on something and then 10 minutes into watching it you're like, "Oh, this is boring. I got to switch to something else."
And this is the friction that we want to take out of the user's way in Google TV. So because I had faced the situation on most Friday evenings or weekends, and so I feel like, "Yeah, I'm going to solve a real problem that I feel like it'll resonate with millions if not billions of users." And so first of all, that resonated with me, so that was super exciting.
And the vision was, I felt was that magical balance between, it's uncomfortable and unknown, but it is achievable. Challenging but achievable because we have access to Google's search algorithms, which are the best in the world in terms of looking at billions of things and bringing you the most relevant thing to you.
So we were on a quest to say, "How can we bring that? We've missed that applying it to the TVs that are in the home in terms of content recommendations." And the second is, I think as a daily user of many Google services, I felt that at Google, we have this unique opportunity to bring a very personalized and very delightful integration of a lot of services, like Google Photos, Google Assistant, Google Search, and YouTube, and many other things together into what's the most best way to use the biggest chain in your home.
And that is something I feel is very unique at Google, that this huge opportunity to do this. And that was our mission. And what we first launched in 2020 with our first-party device, and we have since expanded to a huge number of devices globally.
And what we have seen is our hypothesis was indeed true. Our customer satisfaction, watch time, all the engagement metrics have improved after we implemented this. And we continue to add live TV, sports, all kinds of content, news, but it is, and then regional partnerships, et cetera we have been expanding in many ways, but we haven't lost sight of their core idea which is, "Are we bringing delight to our users? Are we taking friction out of our users' way?"
And so I feel like we have continued to grow tremendously and we're still actively thinking about several of the function innovations to being deeper AI to Google TV.
Caleb Brown:
Yeah, interesting and very fascinating to just kind of hear the evolution of the product and just kind of seeing your vision manifest into a real product. It's very interesting.
Like I said, we were able to chat a little bit before actually recording here and you had a very compelling leadership philosophy, which I believe was hire the best, inspire them, and get out of their way. I really like that. And I wanted to know if you could just kind of elaborate a little bit on how you implement that actually, into practice in your team.
Shobana Radhakrishnan:
Absolutely. I think you started with the part which I think is critical, which is hire the best, because oftentimes it's typical to hire for what I'll call the technical elements of the skill set. And for engineering, it is a certain kind of thing. For product management, it's a certain kind of thing. For an artist, it's a certain kind of thing.
So there are always what I'll call technical skills which are about, can you do an excellent job of the thing you do, whether it's knowing your tools, or how to use them, or how to make presentations and so on? For that's common, but I noticed over time that what is not as common is hiring for DNA.
What does this person get motivated by? What makes this person tick? And I would argue, that disproportionately is what people should focus on, especially for any leadership roles of any levels in your organization. Because as a very small example, in a past role when I was working on moving the availability of our systems to five months, so the TV industry is a very high burn. Nobody wants to restart their TV. We might be open to restarting a laptop sometimes, but nobody wants to restart their smart TV for things to work.
So the availability and all the performance expectations are very, very strict on TV. So I needed someone to come in and really bring a high level of automation so we could be very confident of not just the quality, but the longevity, the durability of the software as well as just uptime, all kinds of factors that are seen as reliability by users.
And I decided to hire someone who didn't just bring the technical skills, but who just woke up thinking about automation, people who would hate doing anything manually. And I really wanted that person and I hired just one person, and this person brought in hundreds and hundreds of tests into the automated suite within just a month. And this is just a small example of how you think about DNA.
And the other element I look for in DNA within engineering leaders is consumer-centric DNA. So I will not say it's very easy, but it's fairly straightforward to find engineering leaders with a passion for technology, but I would like consumer-centric technology passion, and that is another example of hiring for DNA.
In fact, I've had experience where I have either, where I'm told or I have experienced a culture where engineering leaders get on customer calls at least once a week, an actual customer call and listen in as a way of forming that DNA if they don't already bring it, just the customer empathy.
And so I've noticed that hiring for this kind of DNA has again, a huge ... I would say, rather than a ramp-up, such hires make you go through step function improvement as a culture because they may drive for you as a leader what you may not even personally need to drive anymore, just because they're involved in. So those are examples of hiring the DNA.
In terms of inspiring the team, once you bring people who are passionate, excited, and bring the right DNA into the mix, how do you inspire them to bring their best every day, to feel this highest possible energy? Because what I have noticed is when teams are energized by something, they don't even see the hours going and they're working on the initiative. This is true of us. And as someone who's tinkered in your side, I'm sure it resonates for you because you wanted to figure out how to put that phone in a shoebox even though nobody was asking you to do it. I'm sure you spent time and you went late for lunch doing that stuff.
And so that's what I constantly want. Of course, I'm not a proponent of killing work-life balance and forcing people to work weekends and late night, but passion drives energy and it still drives my energy. This has been the truth for me in my personal life. And so I feel like that's where the inspiring comes from, is are we able to match people to what energizes them naturally, which is also aligned with what you're trying to land for your company? How do you do that? How do you make that happen?
Then my experience is you'll notice that you don't even need processes and checklists and all of that as much as you might otherwise need, and the natural energy just makes the team run with the best energy and agility possible. So that's how they inspire.
Now once you've got people with the right DNA, right energy, tied them to the goal, why stand in their way? Just get out of the way, but still be an active unblocker. I feel like your role then becomes active unblocker, or fill the gap. That's how I would say in summary, the approach to leadership that I have evolved and I experience.
Caleb Brown:
Absolutely. Really great stuff there. And one thing that really jumped out at me was I personally believe that more software developers and just engineers should be on those customer calls. I can tell you I worked at a software development company startup that was eventually acquired by Yelp doing wait list stuff. You walk into a restaurant and there's a wait. They put you on the iPad app and text you.
This was a while ago, it was new back then. But something that we had to do, no matter your role at the company was work the host stand at a restaurant and use your own software and see where there were bottlenecks or problems or issues and just understand what the kind of customer experience was, the true customer experience was. And I admit, I didn't want to do it initially. It was incredibly beneficial to see that process actually happen.
The empathy for the customer is so much different when you're sitting behind the keyboard writing code versus seeing it in the real world. And so I just really wanted to point out that I love that you mentioned hearing more customer service calls and just tackling a little bit more of that empathetic side on the development.
I wanted to talk a little bit about kind of how you ... It's sort of on topic with what we've been talking about, but how you kind of balance giving teams that autonomy while assuring that alignment with the broader organizational goals and things like that. I wanted to see if you could expand on that a little bit from the previous conversation.
Shobana Radhakrishnan:
Absolutely, and this is one of the balances that's very tough to strike because it also depends on what your team perceives as sufficient direction and sufficient level of oversight versus micromanagement, or on the flip side, just unclear direction with too much hands-off. So it's the tough balance and it also needs to be tailored to what your teams need.
So I would say that giving a clear direction in terms of, "Where are we marching in the next two to three years or three to five years?" Whatever your team considers medium to long-term, and this is very different based on products, right, because for a hardware, the minimum is maybe two years to develop, or longer. But for software, for example, like software we write, we deploy every day.
So the direction is different, but you need to be able to give clear direction at least for the medium to long-term within which your leaders can then evolve the tactical strategy for execution. So I think each leader needs to consider that their direct responsibility. So that's your hands-on role. There is a hands-on role at all levels of leadership, but how do you bring your team along, I think can vary because in my case, usually we have an offsite where my directs are part of evolving this vision, or sometimes even need to report to them. And that works well for us because that's how we want to evolve it.
And then finally, distill the leader's responsibility, to put it down, to share it out. But these are ways of bringing your people along on a journey depending on how the culture is. And I think beyond that, there's a lot of innovation that can be bottoms-up or grassroots, even fundamental step function ideas can come from anyone in the organization, is my experience.
So rather than focused on titles and levels, just opening the door for ideas to come through. For example, I have two mechanisms to do this. One is, I hold round tables where I have groups of 10 people from across teams doing lunch with me. And so within a quarter, my goal is I've met everybody at least once in such a round table. And it's just the lunch session, so people are very openly talking about things or expressing concerns or giving candid feedback, tough feedback, and that's what I want.
And a lot of times, I notice that ideas come from that, that then I take it to my staff meeting and then discuss and we are making fundamental shifts in how we do things.
The other thing I have done, which has worked for me. It may have worked for others too, is office hours. So I have a mechanism where people anywhere in my organization can book calendar slots easily to have a 20-minute chat with me anytime during the office hour slots. And usually there are multiple, where oftentimes I notice I end up learning more than they do, I think, where they come up with ideas and they're talking about top-of-mind concerns on their mind which helps me think about the team culture as well, often. But I do get a lot of new ideas and then I end up just connecting people with energy and then letting that idea bundle up and become part of a vision.
So I think those two mechanisms for vision. And then within that, a lot of freedom for your teams to figure out, "What are the five things I do, and how do I do them to hit that goal and vision?" So set a North Star, set the point B and then let there be iteration on the how, and in what ways to reach it, but then keep that flow of communication with peers as well as up and down so that you're constantly iterating the path to point B and to the North Star.
And I don't need to mention in this macroeconomic climate that even the North Star may have pivots during the journey, and you all need to be prepared for that.
Caleb Brown:
I wanted to pivot just a little bit into the more kind of technical and innovation side of the leadership and even talk a little bit about the products at hand. I'm just curious, I wanted to get into the AI stuff.
Obviously, a big topic, but for a reason. I think many of us are now using AI in our everyday life. Interested how you're leveraging AI and GenAI to transform the full television experience at Google.
Shobana Radhakrishnan:
Absolutely, and I will start by talking about a couple of features that we just announced at the Made by Google event earlier this year, which we are thrilled to see very positive reception across the board. And our first-party device that we recently launched, Google TV Streamer opened to very high reviews and ratings as well, which we're excited about.
So, two specific examples of features we have already leveraged. The first one is, as I mentioned earlier, the main goal we are setting out to do is, how do we remove friction from decision-making for users to find great content? And we put LLMs to use there.
What we have doing is we are using AI Overviews to bring a summary of what users are saying around the world about the movie. Instead of someone going on Wikipedia looking for user reviews, IMDB, Rotten Tomatoes and then trying to figure out what people are saying, we try to bring in a crisp summary, which you can see on the top page.
So as you're seeing the title description, cast and crew, you can easily see a summary of what people are saying about it. You can, in a click or two, you can see what are people saying about whether it's kid-friendly. And we are not talking about the rating, the official rating, but what are people, parents who have actually watched, saying about it.
So things like that, which may have taken a long time to research or maybe you're asking friends about it, this just comes to you in seconds on the same screen. And so that's one big feature we're excited about.
And the second is just on the screensavers. Your TV is your biggest screen in the living room, and we have a mode called Ambient Mode whereby it's an idle mode. We bring a screensaver on top of the screen, which is a beautiful, natural picture, or it can be a picture from your Google Photos album from a recent event. And so we have leveraged GenAI to make these experiences really great on this big screen.
And another small one I will add, is we notice that our users have better satisfaction and engagement when we describe just above a row of recommendations, why we are bringing this to you, because they feel they are in control because we are giving them an explanation.
So we've also used GenAI to generate the description dynamically using GenAI. So these are just some examples of things we've launched.
Caleb Brown:
Very cool. Yeah, yeah, and I was taking a look a while ago and they really are. It truly looks like great products, great hardware. So, really happy to hear the inner workings of things. And speaking of which, I was wondering if you could share an example of a technical challenge that really required significant innovation to solve. And obviously, that would be great if it was here at Google TV, but we don't have to limit that. I just wanted to see if we could hear more of the story, of the journey of technical challenges that you may have faced.
Shobana Radhakrishnan:
Absolutely. I think there are multiple examples of where I've experienced this, but why don't I stick with the Google TV's example because of recency. And also, probably the highest complexity among many complex examples, that as our vision outlines for us, how do we leverage this world-renowned Google search algorithms and bring them to simplifying content recommendations for users?
And it may sound on the surface like, "Oh yeah, this algorithm already exists." Maybe you spend a few days building this stack and it's just going to work. Right? But this was a multi-quarter initiative and here is why, because with TV, you need to bring very high bar on credibility, accuracy, privacy, security, all of these, which we take seriously across Google for every single product. But with a TV, the users have given you permission to come into their living room.
So, everything the TV plays, everything the TV displays, you'll restrict it to an adult app for it. The kids are walking in the room, there is a three-year-old, potentially in the room, a 10-year-old, a 15-year-old. So we take that responsibility very seriously. That's one angle that's very immune to TV.
And the second is what people tend to search for on the web or on their phone doesn't naturally apply to TV. As an example, if I saw some kind of news, let's say this morning that says this actor was awarded the Academy Award, then I'm going to browse for their name and their movies, but that does not mean I'm going to watch them at home that day. I'm just looking for them. So this is a small example of why search habits don't naturally translate to TV-relevant consumption habits.
Caleb Brown:
That definitely makes sense. And right, from an outsider's point of view or maybe someone not super technical, Google's got all this amazing technology. You can just plug in a TV device and you're good to go. And there's so much engineering to make that, even if you have the best data, you have to make it work for your product. And that can look incredibly different than what it was originally built for, or other things that Google has engineered.
So, I think it's always valuable to bring folks these in-depth conversations about how difficult it is to launch a whole new product even if you're in a very good position like Google is. So it's very fascinating to hear these things.
I wanted to talk a little bit more ... We talk a lot about continuous learning when we're talking about everyone, but we talk about it a lot with our engineers. We do a lot of education at X-Team, and you had emphasized the importance of being a constant learner yourself. And so I wanted to know how you model that behavior for your teams.
Shobana Radhakrishnan:
I think continuous learning is really critical for anyone on a professional journey, but anyone in a leadership role, to set a culture of learning and to demonstrate that you are also constantly trying to learn. I think that I would categorize learning into two broad views. One is, I call it internal learning. The second is external learning.
To me, external learning is about acquiring new skills, looking at new technology. Just yesterday, I was reading a paper from Princeton on LLMs and to get accuracy with best cost optimization for LLMs. And I found it interesting enough that I just shared the paper and takeaways with the team. And that's just a small example because this is something I'm learning not just because my job needs it, because I just love this space, also. And so this is an example of external learning.
And now the internal learning, to me can be both planned and organic. As an example, my team and Google has a culture of what we call blameless postmortems. So every time there is a major production issue, there is a very structured postmortem style, which is blameless element is highly emphasized, which I personally love. It's a very methodical way of saying, "What did we learn from this? What are we applying so this doesn't happen again?"
And I think every year should be zoomed in and actually read such documents. Even if you're not reading it in detail, at least skim over, because I feel like every time I read one of these, I learn a lot myself.
And the second is learning through just feedback from your organization. I mentioned mechanisms like office hours and round tables. There are also structured ways you can get surveys, or you can just do a team check in with your staff at your staff meetings. So make sure you're also, always learning about the team, what's working, what's not working.
And the third element is, we have structured learning series in our ... where people can come and present and people can come and share things that they have learned in terms of technology, or product, or process, or just the business that they bought through. And I think encouraging some series like that and having someone excited about it to really take lead and organize it, so the energy keeps going. I think these are some mechanisms I have seen, beneficial for internal. But always be prepared to learn in every one-on-one conversation you have. Every meeting you have, come in with a mindset to learn. So that's the organic learning part.
Caleb Brown:
Absolutely agree, and great takeaways there, and love when you do my job for me because my next question was about if we could talk a little bit about blameless postmortems. And so I appreciate that you kind of covered that in our last one, which means as we kind of wind down, I want to switch a little bit over to kind of a future outlook questions, just a couple of questions here at the end to just understand where you're thinking, where you're going with looking forward.
And so the first one I had for you was just about how you see AI continuing to transform, specifically the entertainment industry over the next few years.
Shobana Radhakrishnan:
Absolutely. I think AI is going to fundamentally change the way we do entertainment in many ways, and many ways that we have not even foreseen yet. We are just getting started and scratching the surface is what I strongly believe. I think this could be in the form of generating creative writing, which many articles and discussions have talked about already.
So first let me say, I don't see AI as removing jobs or taking away jobs. I see it as modifying the job definitions. We are going to need the same number of people or probably even more people as this expands, is what I think. But the way we look at job descriptions and what people do is going to evolve in ways that are different from current.
And so it can start with things like creative writing and generating content, but also generating text to image, text to video, text to audio and bringing voiceover as in terms of interactive voice or it can be in terms of, you speak with a voice that understands you and there's an agentic interface that talks with you and makes it very personal for you. Or it can be that you're able to generate content in one language, and instead of spending months and months converting it into global content, whether it's live captions or voiceover or dubbing, maybe it's just going to be minutes.
And so there is drastic productivity improvement, I think that will happen in the entire entertainment industry. And then we also usher in, I feel, an era of more inclusive, more globalized content because accessibility, which may take months, and many corporations may not even be able to effectively prioritize accessibility and global inclusion, this could become a reality in just minutes where everyone builds global products, and the local audience is just as enamored as the audience in your primary markets. And so I think the global play in entertainment will go huge steps up because of AI.
And the other element I'll say is, I think more and more we're all having cross-device journeys and cross-device lives. We all have so many devices at home and personally, and entertainment is going to be even more seamless than it already is, and even more ubiquitous.
But I think AI will help generate a sense of continuity and interactivity journeys irrespective of which device you're engaged with. Just based on where you're walking, where you're riding versus you having to use your touchscreen to say which device you're on and engaged, there's going to be a lot more listen, understand and interact, I think because of AI.
Caleb Brown:
Last question for you, one that I like to typically ask most guests. If you could wave a magic wand and kind of change one thing about the tech industry, what would that be?
Shobana Radhakrishnan:
I will say democratizing technology and access to knowledge. So, make it available to every single person in the world somehow. But this is multipronged, so anyone who's connected to the internet should have access to the same thing that I have access to sitting here in The Bay Area.
And this is something that's very close to my heart, is I volunteered when I was a teenager, a kid in trying to bring education to different corners of India, going to remote villages. And so this is something that brings chills to my heart throughout my life, is democratizing knowledge and technology.
Caleb Brown:
Absolutely. Something I've always found beautiful about Silicon Valley and the tech world, particularly Google and Meta and companies like that is advancing that, right? We don't have it yet, but I think we're closer than we used to be. So I think that is a very good wish of the magic wand.
And yeah, thank you so much for all of these insights. It's a really enjoyable conversation. I learned a lot. So, thank you so much for joining us today.
Shobana Radhakrishnan:
Thank you, Caleb. It was amazing speaking with you. It was a true pleasure.
Caleb Brown:
What an incredible conversation with Shobana about leadership, innovation and the future of AI-driven entertainment. One of the biggest takeaways for me was her leadership philosophy, hiring the best, inspiring them, and then getting out of their way.
Her emphasis on fostering a culture of autonomy while ensuring alignment with broader goals is a powerful lesson for any leader looking to scale high-performance teams.
I also loved hearing about the evolution of Google TV and how her team is using AI to create a more seamless, personalized, and engaging entertainment experience. Her insights on balancing cutting-edge innovation with real user needs, especially in a product that millions interact with daily, were fascinating.
And finally, her perspective on continuous learning and democratizing access to knowledge was inspiring. Whether through structured learning, open dialogue, or hands-on customer engagement, she's leading by example in a rapidly changing industry. Thank you, Shobana for sharing your journey and these invaluable insights. And thank you, to our listeners for being part of this conversation. It's stories like these that remind us why we keep moving forward.
Join us next time for more insightful conversations with tech leaders who inspire us to grow, lead and innovate. Find us on Apple Podcasts, Spotify, or YouTube Music. And don't forget to share this episode if it resonated with you. Until next time.
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