The Exchanges

Q Toma, what's the most controversial product decision you've made?

A If I go back, the feed at LinkedIn, um, you know, now in hindsight doesn't seem controversial, but at the time it was very controversial. So, uh, just to give some context and maybe to take a step back, there's a lot of discussions usually about zero to one product and the launching and how to scale product. There aren't many conversations about minus one to one product, product that we're not doing really well. And there was a turnaround story. And for me, the LinkedIn feed is a good example of that. Uh, LinkedIn was actually one of the first social platforms to ever have a feed, but it was more of an activity feed. It was a connections feed, the jobs updates feed, the profile views feed. In 2015, for the first time, we assembled a feed team at LinkedIn, and we focused on creating an experience, which is all about professional conversations. Now, again, that sounds You know, clear in hindsight, but back then that was not a thing at LinkedIn. Uh, the feed was really a promotional feed for teams to showcase their products. So, you know, the growth team would show people you should, you know, you should connect with. And the jobs team would show jobs you might be interested in. And everybody was using the feed as a promotional way to show members, um, recommendations about that they can do across LinkedIn. But there was no opinion that the feed was about professional conversation…

AI assessment note: “the feed at LinkedIn, um, you know, now in hindsight doesn't seem controversial”

Q You mentioned that the buying decision and actually kind of the influence that one has. I'm too interested. I had Glenn Coates on the Show who's, uh, who is VP of product at Shopify. And he said that the day that the founder is no longer the CPO is the day the company stops innovating. Is that fair?

A I think the context of the company matters a ton. It really depends on the stage and, you know, founders, in my opinion, I love founders. They're a critical part of every life cycle of the company. Because they intimately carry the original vision. They have that birthing insight that made the company, and that's invaluable. Now, some of the best companies in the world that their funders do not play an operating role, like Microsoft or Intuit or Netflix right now or Amazon, the founders are still playing a guiding role. So they're still there for, you know, Bill Gates at Microsoft, Scott Cook at Intuit. Bezos at Amazon. And those are very successful companies. You know, Apple still has the spirit of Steve Jobs, but obviously he's no longer there. So I think it really depends on the stage of the company. Personally, you know, working when I joined LinkedIn, Reed no longer had an operating role. He was our chairman of the board, but I spent a lot of a one-on-one time with him. Um, so I think it's having the founder as part of the company and always laddering up to that Uh, that founding insight. I like to think that companies have founding moments, and it's more than one. If the company is successful, LinkedIn is going to be 20 years old, 20 years old in a month from now, actually a couple of weeks from now, we're going to be 20 years old. And I think the company went for multipl…

AI assessment note: “I think the context of the company matters a ton. It really depends on the stage”

Q Listen, I could talk to you all day. I didn't know you're a runner as well. So like, fuck, we're in for a long session. Um, my final one for you though, is what's the most recent company product strategy that you've been most impressed by?

A So this is a very easy one, but I'm obviously very subjective, so you have to excuse me on this one. I've been very impressed with what Satya and Microsoft has done with the OpenAI integration. It's just hard to look at it and not, uh, be impressed by the strategy, the execution, uh, the impact. I've been able to see it firsthand, be part of it firsthand, and I know what's about to come and I'm extremely bullish about it, but being able to Really think through a groundbreaking technology. Think through the execution of taking it to market in a responsible way. Thinking through the elements of all the way from cloud impact to productivity to end user. For me, that's one of the, one of the most impressive product strategies I've seen in a long time. Plus execution. Been remarkable to see and be part of it.

AI assessment note: “I've been very impressed with what Satya and Microsoft has done with the OpenAI integration.”

Q It totally does. I'm just thinking it through. Uh, my, what, what I also think through when I think of that is shit, AI fundamentally fucking changes how we build products. Do you as a product leader need to fundamentally change how you lead product teams and product organizations with AI moving faster than ever, as we touched on when we chatted before?

A Yeah, this is something which is dear and new to my heart because I've been working, uh, on AI with AI for many, many years. And, uh, same as we had the mobile revolution happening, um, kind of, 15 years ago and how we changed dramatically how we build and how we use products. AI is going to be much larger. In fact, I think every tech revolution has dramatically changed the way we build and how we think about products, you know, from the PCs in the seventies, the internet in the nineties. You had mobile in the first decade of the 21st century. And AI is going to be the biggest one we ever experienced. And if you're building product today, I have this analogy that when you have a rear rafting boat, you have the guide on the boat sitting on the back, and that guide usually has two big pedals. And those pedals pretty much navigate the boat. They pretty much dictate success or failure for your product. And those pedals for me are AI. And that guide better be you as the product leader. So if you lead products in your company, you have to have the knowledge and skillset to know how to use AI, how to use those pedals to navigate your team and your company towards success. So it's a critical fundamental change right now.

AI assessment note: “So it's a critical fundamental change right now.”

Q Speaking of that conviction and data, I do want your advice. Product reviews are so cool to all product teams and to all companies. How do you do product reviews? How often do you do them? Who's invited?

A Yeah. So we do multiple product reviews every week. It starts, um, each quarter. We actually kind of review all of our big rocks, our big investment areas across the product and the business. And then, uh, we determine what do you want to see as a product team coming in? And for that, I decided what's the products I want to, you know, cover for review. But for context, I don't call them product reviews. Uh, I call them product jams and there was a very specific reason for it. Uh, we used to call them product reviews and people used to see it as a way to get almost like, um, you know, uh, um, a, you know, a pat on the back for whether it was a good product review or if you got feedback, it was a bad product review. And It really took away from building a great product. So in a growth mindset notion for me, those sessions are all about feedback. So I changed it to be product jams. And what I tell the team is you've put your best thinking forward. You know, you worked hard on the product. You worked hard on the thinking. You worked hard on the design. Now you're putting it to the team. And our goal as a team in this meeting is to make that thinking better, is to make that product better. So the only currency really is feedback. And what's nice about this team is you really have kind of this three 60 You have the team presenting. They provide that local expertise. They're the one w…

AI assessment note: “we do multiple product reviews every week”

Q like, boom, come alive. It's great. It's so, I love it when you have This is why I love doing what I do. Like the conversations you have are just special. So I want to do a quick fire round and then I'm going to let you go. So I say a short statement, you give me your immediate thoughts. What is your favorite interview question when hiring for product?

A I like asking two questions. Uh, that's kind of my stable, my, my kind of table stakes questions usually. One is what's the most complex problem you worked on? And how did you do it? And what you are trying to understand there is what was your job to be done inside? How clear you are around expanding a complex problem? How new ones can you get? Uh, how profound, how much of a profound understanding did you bring to it? And I enjoy going deep. I really enjoy going deep with, uh, with candidates. The other one is a growth mindset question. I'm looking for areas where you did not succeed, where you failed. Understanding how you dealt with that. How did you deal with failure? And I'm looking for learnings. And the best responses I get is I've learned so much and here's how I've done differently. And, and it's not, um, it's not about retroactively trying to fix anything. It's more about seeing that there is a, an evolving mindset there of trying to do things better and better and evolving over time. Those are kind of my two main questions I ask in every interview.

AI assessment note: “One is what's the most complex problem you worked on?”

Q of feel a bit ridiculous sending them off to school every day? And I don't mean that rudely, but I just mean in like the decay rate of education. It's like, by the time there'll be like functioning adults in the workplace, I don't know how old they are, but say it's 10 to 15 years. I mean, fuck. You know, well, What they're learning today is pretty useless, huh?

A I think the only skill, the most important skill outside of being a good human being and a kind human being, but from a, uh, from a, what do you learn to be successful? The only skill that matters I think is growth mindset. It's the ability for you to learn, to continuously evolve. I think we're moving to a place of, you know, you're already at a pace of accelerated, um, uh, technology. Like if you look at the skill set you needed for a job today versus five years ago, that has changed by 25%. So a quarter of the skill set required five years ago, no longer, they're different right now. You look at it five years ahead, they're going to be 50% different. And we all know they're going to accelerate and accelerate over time. So then you go back to, is it learning a specific skill? Should you learn coding? You know, what should you learn? And it's really, for me, it's, you should learn how to learn. You should learn how to Pick up new dimensions and new material and new areas as fast as possible and being able to immerse yourself with it. I think that's the most important, at least for me in my household and, you know, growth mindset is like our second religion at home. It's the most important thing we invest in.

AI assessment note: “The only skill that matters I think is growth mindset.”

Q Speaking of that conviction and data, I do want your advice. Product reviews are so cool to all product teams and to all companies. How do you do product reviews? How often do you do them? Who's invited?

A Yeah. So we do multiple product reviews every week. It starts, um, each quarter. We actually kind of review all of our big rocks, our big investment areas across the product and the business. And then, uh, we determine what do you want to see as a product team coming in? And for that, I decided what's the products I want to, you know, cover for review. But for context, I don't call them product reviews. Uh, I call them product jams and there was a very specific reason for it. Uh, we used to call them product reviews and people used to see it as a way to get almost like, um, you know, uh, um, a, you know, a pat on the back for whether it was a good product review or if you got feedback, it was a bad product review. And It really took away from building a great product. So in a growth mindset notion for me, those sessions are all about feedback. So I changed it to be product jams. And what I tell the team is you've put your best thinking forward. You know, you worked hard on the product. You worked hard on the thinking. You worked hard on the design. Now you're putting it to the team. And our goal as a team in this meeting is to make that thinking better, is to make that product better. So the only currency really is feedback. And what's nice about this team is you really have kind of this three 60 You have the team presenting. They provide that local expertise. They're the one w…

AI assessment note: “we do multiple product reviews every week.”

Q What's the biggest piece of advice you give to a new product leader joining an organization today? What do you wish you'd known when you, the night before you became CPO of LinkedIn for the first time?

A I think when somebody joins a PM at LinkedIn and usually ask me like, what's my, what's the best way for me to be successful? The biggest thing that I tell them is, you know, if you just focus on your area, there's a chance that you'll be linear successful and you can move your area forward and can hit your targets. But really your ability to be exponentially successful at LinkedIn is really learning how LinkedIn works. LinkedIn is a beautifully complex ecosystem. We have a consumer platform that caters to nine hundred million members, sixty million companies on LinkedIn, almost every job and skill in the world on LinkedIn, almost every piece of professional knowledge and information is on LinkedIn. Now with that ability, How can you build something that is truly unique? It's truly innovative, but don't just think about your swim lanes and what you're trying to do. Think more holistically about the experience that you can bring into it. Some of the best experiences on LinkedIn, they cross across the entire ecosystem, across multiple products to build something which is really unique. And that's where I would love to see innovation come through, not how I innovate within my specific area of my future.

AI assessment note: “really your ability to be exponentially successful at LinkedIn is really learning how LinkedIn works.”

Q Can I ask an interesting one, which is like, I think, you know, both TikTok and Facebook have realized kind of the decaying utility value of social graphs for them and moving to kind of content recommendation engines. You mentioned that advice, inspiration, motivation of posts. To what extent do you think you're moving to, to the content recommendation engine over the social graph component?

A I think the social graph for us has been a phenomenal construct for you to be able to almost like, you know, tell us who are the people that you find most valuable in your network, in your career. And again, your network is how you get things done in your professional life. That's the founding insight of LinkedIn. So that will never go away. Being able to say, those are the people that matter to me. Those are my colleagues, my customers, my clients, the people in the industry I want to learn from. That's a really key part. Of, of gonna be your LinkedIn. Let's call it, you know, conversational experience, not just the feed experience, because the feed could be constraining as a, as a mental structure. The having said that, uh, I think the idea of being able to go more topical recommendations and being able to find people who are outside of the people, you know, but they matter tremendously to your craft is extremely important. So I could be an AI engineer in the field of agriculture right now and say, who are the best AI engineers working on crop development systems? And I might not know them personally, so they're not part of my network, but being able to follow them, to learn from them could actually change the trajectory of my career. I can do a much better job. I can.

AI assessment note: “So that will never go away... having said that, I think the idea of being able to go more topical recommendations”

Q Do you think we need a refresh though? Cause I have 5000 connections. I'm not that connected Toma, despite my desires. Do we need a refresh of connection utility value?

A Well, 5000 is well connected. Um, but I think in many ways, I think when it comes to rebuilding the network, I think, yes, a lot of people are actually going and they're in a way cleaning it back to the people that they are, uh, they know in terms of the network, but ultimately it's hard to do. It's not something that most members would enjoy doing and going and cleaning your networks. What we're trying to do is emphasize the ones that we know there's a strong connection strength with. Uh, people you interact with on a regular basis. People that when they reach out to you, you know, you respond. Uh, there's a bi-directional relationship. That's the idea of connect.

AI assessment note: “What we're trying to do is emphasize the ones that we know there's a strong connection strength”

Q Do you see a difference in product review discussion quality and feedback quality when comparing remote and online versus in-person and whiteboarded?

A I do. I actually do my product jams in person. I feel there is an energy of creativity and discussion that you get in the room in person. It's, you can do it remote as well. It's, there's no, It's not that remote does not work, but I think there is an edge to doing it on a whiteboard, discussing, opening, pointing, having freeform conversations that allow for that creativity and discussion to be a lot more natural. So I move my product jam sessions to be in person. Uh, and with COVID, we moved them to be obviously remote because there was no other way. But once we came back from, uh, from, uh, COVID, uh, we moved it to be in person and across the room, people will tell you the energy levels are just higher. The creativity The ideation, the velocity of discussion just, uh, is elevated to a whole new level.

AI assessment note: “I do. I actually do my product jams in person.”

Q When you have, you know, bluntly this structure and you have a lot of ideas thrown around, you also have to make decisions and you have to prioritize. When you come out of a product review, how do you prioritize what to do, what not to do, and what's a luxury, but next quarter?

A So if we just finished a create product jam, um, then what happens is there's tremendous amount of feedback being shared. As I mentioned, the only currency for those from ER is feedback. Usually the way I end the meeting is I summarize the areas that, uh, we covered and where I would like to see progress on. I try to make sure it's between one to three, so it's not the whole list. Uh, and then the working team, we have a, uh, a new process we started Uh, a while back, which is called brief back. The team itself, which presented, they send a summary of the session with the feedback and all the key action items they have and the ETAs for the key areas they're going to work on. So it's really up to the team presenting to take that feedback and act on it. And we literally have those sessions. That's really allows for clarity and execution back to the point we talked about before. We don't leave a product jam without clarity of what's the next steps and what's the changes you will make as a result of it. But it's really up to the team leading it to go and do it and follow up on it.

AI assessment note: “I summarize the areas that, uh, we covered and where I would like to see progress”

Q Is that an amazing dilemma question? Is it where you've got to cannibalize your existing product with a new product? That's, would you agree?

A A hundred percent. Yeah, because internally it was, it, the feed was a massive discovery engine for so many products at LinkedIn. And it was a revenue engine for so many products at LinkedIn. And in a way for actually for many companies, it was their main discovery channel. So then comes this, you know, um, uh, not confused by, you know, not confused, but might be wrong product leader and says, I'm going to change it. I'm going to change the core of how this works. And, you know, there was high conviction there and I had to show evidence along the way. But that was a highly controversial decision early on. And gradually, as we showed evidence, you really got to a point where you raised all boats. You got people to start using the feed, see it as a place that can actually have professional conversations. And over time, all of those products benefited. But at the beginning, it was a little bit of, um, I need to create space for growth. I have to start trading off some of how we used to be doing things in the past, so I can change it to how we do things in the future. Um, and, but, and the feed is a great example because there's so many inflection points, you know, what, when we started doing that, one of the things we saw was also, we drove, after we started orienting on professional conversations, we start seeing virality take off. And we saw strong engagement and virality, but …

AI assessment note: “A hundred percent. Yeah, because internally it was, it, the feed was a massive discovery”

Q It totally does. I'm just thinking it through. Uh, my, what, what I also think through when I think of that is shit, AI fundamentally fucking changes how we build products. Do you as a product leader need to fundamentally change how you lead product teams and product organizations with AI moving faster than ever, as we touched on when we chatted before?

A Yeah, this is something which is dear and new to my heart because I've been working, uh, on AI with AI for many, many years. And, uh, same as we had the mobile revolution happening, um, kind of, 15 years ago and how we changed dramatically how we build and how we use products. AI is going to be much larger. In fact, I think every tech revolution has dramatically changed the way we build and how we think about products, you know, from the PCs in the seventies, the internet in the nineties. You had mobile in the first decade of the 21st century. And AI is going to be the biggest one we ever experienced. And if you're building product today, I have this analogy that when you have a rear rafting boat, you have the guide on the boat sitting on the back, and that guide usually has two big pedals. And those pedals pretty much navigate the boat. They pretty much dictate success or failure for your product. And those pedals for me are AI. And that guide better be you as the product leader. So if you lead products in your company, you have to have the knowledge and skillset to know how to use AI, how to use those pedals to navigate your team and your company towards success. So it's a critical fundamental change right now.

AI assessment note: “So if you lead products in your company, you have to have the knowledge”

Q to five years. It may be seven out of 10, but it comes in a nice open AI wrapper. We know open AI, that's a famous brand, right? And it all comes under one umbrella. Versus a world of unbundled, many models, a bit more customization, probably better products, but more tailoring and tinkering needed. Do you think we are entering a world of enterprise bundled preferences on AI products?

A You know, there's a great saying in technology that if you look back, you'll see technology as an evolution of bundling and unbundling. And I do think we are potentially seeing the next bundling transformational wave. For me, it's really comes down to the role that AI can play in taking a lot of what was drudgery Um, tasks, automating them, and you'll be able to combine roles together. So if you needed multiple products, multiple roles before to create certain experiences, and a lot of it was just, you know, roles that could be automated. There were jodgery. There were, it's the, you know, the work you do that you would rather give a machine. You would rather have a machine do so you can focus on the creative work, the more managerial work of it. With AI, you can do that today. You can have that master brain working across multiple interfaces, multiple products with the same objective you have in mind. So we are, in my opinion, going into a transformation of bundling when you'll see better, more efficient experiences done by one centralized brain, which is the AI model itself. And in fact, right now already, um, OpenAI showed how by adding multiple services that OpenAI connects with, you can go all the way from, I want to have a, you know, I'll give you a consumer experience. I want to do a dinner party with my friends and I, you know, I'm thinking about recipes, give me a grea…

AI assessment note: “I do think we are potentially seeing the next bundling transformational wave.”

Q absorber of knowledge from smart people, and then I try and kind of amalgamate it together. Everyone tells me that actually every company or the best companies will use multiple models at the same time and transition between them. How will product people be able to have eight different models in use at the same time, know all of them really well to utilize them effectively? How does that look?

A I don't think it's a product, people. I think this is where you build, like, a platform that basically enables you to understand the task you're trying to accomplish. Cost, we should talk about cost at one point because this is a very costly software and costly technology, and then that's actually what you're being masked people with. Uh, you know, deciding what kind of model you use for what purpose really starts at the application layer, but the decision is not made at the application layer. Like that's actually, if I think of like why I would expect to see some massive innovation and startups to show up, it's in this tier to really allow people to leverage multiple models at multiple call centers and resources and efficiencies, and then completely mask it from the developer, from kind of the front, um, like from the designers or the product folks.

AI assessment note: “I don't think it's a product, people. I think this is where you build”

Q Yeah, no, I, I agree with you. Toma, uh, tell me, if you could change one thing about the LinkedIn product today, what would you change that you haven't already?

A Yeah, I think, you know, well, what, what, what's, what's interesting right now, we talked about the idea of UI and complexity. There's this great law that I'm, uh, I really like. It was really helpful early in my career to think about how to build products, which is the conservation of complexity. The idea that every product has an inherent amount of complexity and the idea is you can, you solve it In the product development side, or do you actually put it on the user to solve by themselves? And I think we're in this phase right now where there's so many use cases and audiences that people come to the LinkedIn kind of main app for, and that just had inherent complexity because there was so many, you know, you come in the morning, you're trying to see what's happening in the world. Later in the afternoon, you interview somebody, you want to check out their profile. Then, you know, your boss upsets you later in the day and you want to see what's out there for you. This is all three use cases in the same Like, 24 hours. I think now with AI, and I would claim probably this would be a more generalized statement, the more complex your product, the more impact AI could have in terms of simplifying it for your user base. So one thing that we're already underway for us is to really take away the complexity and solve it with the idea of bringing in more of this new, uh, large language m…

AI assessment note: “to really take away the complexity and solve it with the idea of bringing in”

Q So when we look at stories, we've got snap, like product market fit first and like LinkedIn were very far behind in like race to product market fit on stories. Do you think that was a core component as well?

A Um, I don't think it's the same dimension because we were not trying to compete with Snap. We were trying to see if that format of stories Uh, would allow for better creation and better way to express yourself on LinkedIn. I think what we saw with stories that there was a construct that people bought around, you know, people were really excited about expression that worked really well in Instagram, in Snapchat, uh, works really well with shorts, um, as well. And it, um, you know, that, you know, the evolution from there to TikTok and so on. And for us at LinkedIn is the question is, is that format conducive for professional knowledge sharing? So that was like a test we were trying to, to do, but I don't think it was the notion of being first to the market that made it special. At least not for us.

AI assessment note: “I don't think it was the notion of being first to the market”

Q How do you think about utility value of connections? You mentioned that I might not know them, but I can follow them. I probably get. 200 connection requests a day from people. I don't know. How do you think about like how much value a connection actually means today, given that awareness?

A So it's a great point because I think that's one that it took us, uh, quite a while to solve for members. We started with just connect. As a construct, because it was about people you knew that were part of your network with the idea that you can reach out for help. And, uh, they're willing, there's a kind of a bi-directional desire to help each other. Um, and then we introduced the idea of following people quite later in the role. And we, we never did a great job clarifying the role of those. And I think we are right now, but, um, I think that led to people building networks of people that don't necessarily know really well. But they love to learn from, which would be a follow relationship. So for example, now when you go to the product, uh, we would suggest that you follow people who are not necessarily, um, we don't necessarily think you have a relationship with. Like if you went to the same school together, same year, You work at the same company in the same years, we might suggest you connect, but if not, we'll suggest you follow people. And that's something we're continuously working. Actually, follows right now is one of the most impressive growth trajectories at LinkedIn. It's growing at 200% year over year. There was no for a billion follows a while back or so. It's been grown a lot since then, but it's really honing down that there's Two kind of modalities of relation…

AI assessment note: “Two kind of modalities of relationships on LinkedIn. There's your network that you're willing to help”

Q When you have, you know, bluntly this structure and you have a lot of ideas thrown around, you also have to make decisions and you have to prioritize. When you come out of a product review, how do you prioritize what to do, what not to do, and what's a luxury, but next quarter?

A So if we just finished a create product jam, um, then what happens is there's tremendous amount of feedback being shared. As I mentioned, the only currency for those from ER is feedback. Usually the way I end the meeting is I summarize the areas that, uh, we covered and where I would like to see progress on. I try to make sure it's between one to three, so it's not the whole list. Uh, and then the working team, we have a, uh, a new process we started Uh, a while back, which is called brief back. The team itself, which presented, they send a summary of the session with the feedback and all the key action items they have and the ETAs for the key areas they're going to work on. So it's really up to the team presenting to take that feedback and act on it. And we literally have those sessions. That's really allows for clarity and execution back to the point we talked about before. We don't leave a product jam without clarity of what's the next steps and what's the changes you will make as a result of it. But it's really up to the team leading it to go and do it and follow up on it.

AI assessment note: “I summarize the areas that, uh, we covered and where I would like to see progress on.”

Q they're generic, but I, I'm fascinated on this one always, which is like, when we think about products today, especially given your experience working kind of within semiconductors, within consumer, and then also kind of like incumbent LinkedIn style, like, do you think product is more an art or a science? And if you were to put numbers on it, attach it to them, where would you put it, Toma?

A So I heard you ask this question on a previous podcast I listened to, and I must say it created some tension for me. Because I think it's impossible to delineate science from art. I think they're interroven. They play off each other. There's a lot of science in art. Like my daughter, my ten-year-old daughter loves art, and now she's learning about scientific principles of geometry and color theory. And there's a lot of art in science. Some of the best scientists in the world are very imaginative. But after I kind of, uh, thought about it more, I think when we talk about science in product, I think there's a tendency to think about it more as the best practices of product, the skill set. How do you learn, you know, the know-how around design and data and experimentation and business. And that for me is a foundation of what it means to be good at this job and honing that craft. The scientific part of it in quotes can take you a long way, and it has to be applied learning, right? You can't sit in a classroom learning how to do product. You have to build. But I think what sets you apart in the craft of building product is your ability to bring vision and creativity and intuition and the judgment and the imagination. I talked about my interaction with Reed. I think that's what sets you apart from the group. It's where you listen to customers or users, or you just observe them. And s…

AI assessment note: “I think it's impossible to delineate science from art. I think they're interroven.”

Q years of healthcare data that you can, you know, bluntly utilize the models on. Where it then is actually 30% open AI or 40%, whatever it is, and 60% new. But this thin layer of, I'm seeing so many sales tools, onboarding tools, human, or I don't think value accrues onto that. And so I'm like, where does value accrue then in this wave that you mentioned? I'm an investor.

A So if you ask me a couple of years ago, I would have told you that data is everything in AI, right? Because computing power is accessible and, and the models are accessible to all the open source. So it's really about the data you have. And, and there was a, you know, people coined data as the new oil, and there was a reason for that data was the fuel. That helped AI become better, and then the more data you had, the better products you can build, the better products you have, the more users you have, the more data you have, and you have this virtuous cycle of success. It was also vicious cycles for startups. A startup has to innovate around how do we get data, and there's ways to do that as well, by the way. Some very amazing scrappy startups were able to bring data in a very innovative way that helped them compete. Now, what's happening right now is, you know, technologies like GPT are already trained on all public data. They've read every book, every healthcare book. They've trained on every piece of literature, art, best practices. This, the whole idea of the pre-trained is one of the biggest inflection points of this technology. It's already trained on every available public information out there. So the data advantage that used to exist a couple of years ago, I think is getting diminished. But not to a full extent, because to your point, you can still bring your own propr…

AI assessment note: “the data advantage that used to exist a couple of years ago, I think is getting diminished”

Q If we, if we go deeper though, clarity of vision, you know, you might, you might be wrong, but you're not confused. Let's go deeper. What is driving the growth? Is it the feed? Is it the newsletters? Is it messaging? Where, where is the clarity that is driving growth?

A So I think if you look at LinkedIn, ultimately it comes down to when I open the app, I'm able to, ah, more progress is my job to be done. And it could be that I'm coming in and I see Harry Stevens on my feed and I learn a new insight and I want to follow what he says and I want to follow the people he talks to so I can learn more about my craft and be better at it. But at the same time, it could also be, we know whenever I need to go to LinkedIn because I'm about to meet somebody, I can get the insights I need. To have that interaction, but be more deeper, be more meaningful. And we all meet people on a regular basis. So ultimately the feed, the messaging, those are just constructs to help you accomplish your job to be done. But I think it starts with that clarity on what is it that you're trying to get done. So we know that people come to LinkedIn to come to the LinkedIn feed. They're trying to find ideas, advice, inspiration. They're trying to see what their network is up to so they can start continues to build relationship. And those out ladder up to a job to be done. They have. So it's not a specific area of the product. It's the experience that allows you to fulfill your needs.

AI assessment note: “So it's not a specific area of the product. It's the experience”

Q to five years. It may be seven out of 10, but it comes in a nice open AI wrapper. We know open AI, that's a famous brand, right? And it all comes under one umbrella. Versus a world of unbundled, many models, a bit more customization, probably better products, but more tailoring and tinkering needed. Do you think we are entering a world of enterprise bundled preferences on AI products?

A You know, there's a great saying in technology that if you look back, you'll see technology as an evolution of bundling and unbundling. And I do think we are potentially seeing the next bundling transformational wave. For me, it's really comes down to the role that AI can play in taking a lot of what was drudgery Um, tasks, automating them, and you'll be able to combine roles together. So if you needed multiple products, multiple roles before to create certain experiences, and a lot of it was just, you know, roles that could be automated. There were jodgery. There were, it's the, you know, the work you do that you would rather give a machine. You would rather have a machine do so you can focus on the creative work, the more managerial work of it. With AI, you can do that today. You can have that master brain working across multiple interfaces, multiple products with the same objective you have in mind. So we are, in my opinion, going into a transformation of bundling when you'll see better, more efficient experiences done by one centralized brain, which is the AI model itself. And in fact, right now already, um, OpenAI showed how by adding multiple services that OpenAI connects with, you can go all the way from, I want to have a, you know, I'll give you a consumer experience. I want to do a dinner party with my friends and I, you know, I'm thinking about recipes, give me a grea…

AI assessment note: “I do think we are potentially seeing the next bundling transformational wave.”

Q with them, and I got it back by ChatGPT in about six seconds, and I was like, well, that saved the learning process. I just read that one. Um, so, so yes, I, I totally get you. Final, final one, I promise, and then I'll do a quick fire. Is it a world of one model? Or is it a world of many models and much more complexity, but tailorization?

A I think it's a, we are now in a phase of like foundational models. So the foundational sets the baseline for all other models to build on top of it. So you'll see a lot of applications and new models. There is now like auto GPT that takes the GPT-IV and builds, uh, kind of, uh, overarching, um, kind of, uh, objective function above it that kind of breaks it down to multiple subtasks. So I think we're now at the phase of foundational models and you'll see a lot more applications build as a result of that on top of it. Uh, and then gradually we'll see more and more foundational models in the future. So you're going to start, you know, back to the notion around bundling and unbundling. I think we're now in the version of like unbundling to multiple versions until we see another foundational model in the future.

AI assessment note: “So you'll see a lot of applications and new models.”

Q absorber of knowledge from smart people, and then I try and kind of amalgamate it together. Everyone tells me that actually every company or the best companies will use multiple models at the same time and transition between them. How will product people be able to have eight different models in use at the same time, know all of them really well to utilize them effectively? How does that look?

A I don't think it's a product, people. I think this is where you build, like, a platform that basically enables you to understand the task you're trying to accomplish. Cost, we should talk about cost at one point because this is a very costly software and costly technology, and then that's actually what you're being masked people with. Uh, you know, deciding what kind of model you use for what purpose really starts at the application layer, but the decision is not made at the application layer. Like that's actually, if I think of like why I would expect to see some massive innovation and startups to show up, it's in this tier to really allow people to leverage multiple models at multiple call centers and resources and efficiencies, and then completely mask it from the developer, from kind of the front, um, like from the designers or the product folks.

AI assessment note: “I don't think it's a product, people. I think this is where you build”

Q Can I ask, you mentioned your relationship with Reed there. What would you say is the biggest lesson or takeaway that you've learned from Reed in that relationship?

A I love my one-on-ones with Reed. Usually I come with an agenda and we somehow find ourself going very deep on one topic, uh, that I haven't even thought about. I, I think of Reed as my, you know, I would come to Reed and I'll say, Hey, there's option A and option B and help me think for those. And he'll give me option orange that I haven't even thought about before. And it's highly philosophical. It's, it's really deep. It's really insightful. So most of the time we, We kind of stay at this level of, of insights and, uh, profound understanding of needs and talking through those versus the details of, of the product itself. I, I come a lot for read when there's a really complex problem I'm trying to solve or trying to be inspired with a whole new way of thinking. Uh, that's kind of my source of, uh, of product inspiration in many cases.

AI assessment note: “he'll give me option orange that I haven't even thought about before”

Q of the internet. Sounds great, but guess what? It means fuck all to that SMB who just needs to make 10% more money so they can buy that coffee machine. The GDP of the internet? Intellectual. Too much. Like, do you worry sometimes that LinkedIn at the scale and incumbent size you are, you almost lose product messaging touch with fuck. I actually just need another client as a freelancer.

A It's, it's a wonderful point and one that, uh, kind of touches on why in product jams we emphasize the job to be done you're trying to hire for, you're trying to do for. So for example, even if you're solving, you're saying, even if, for example, you selected the job to be done for a job seeker, there's so many jobs to be done for a job seeker. You could be building, you know, a job seeking experience for people who are looking for hourly work. You're trying to find a job for people who are, you know, playing more in degrees that, you know, they're more professional hires in the market itself. You're trying to find jobs for what we call first line hires or people out of school. We're trying to find for the, for the same time. So for me, being able to talk specifically, not just on the audience and the overall arching, um, Value proposition you're trying to deliver for them, but going very narrow to the problem you're trying to solve is key. When you have that, then you're not trying to solve for everybody. You have very specific jobs to be done, you're solving for people, very specific audiences you're solving for people. Now, all that is up to the vision. So after a while, once you think you've done a good job with that job to be done, you can move to the next level. So for example, at LinkedIn, one of our fastest growing segments are Gen Z's and entry level professionals. So …

AI assessment note: “why in product jams we emphasize the job to be done”

Q here. I'm going to get you in trouble with comms, Toma. But LinkedIn is a publishing engine as well. I publish to LinkedIn my posts. Many people publish amazing content to LinkedIn. OpenAI and ChatGPT in many of these models will be scraping and extracting your content and your value. Paying you nothing. How do you think this looks for content publishers moving forwards? What's the, what's the thoughts there?

A Yeah. I think LinkedIn is a platform, uh, that allows people to exchange information in many ways. We actually open up, um, discovery for information being shared on LinkedIn, because it's a great way for creators to be able to be discovered. Outside of LinkedIn and then, uh, they can build the reputation on LinkedIn and being know they can be discovered everywhere. I do think though, you know, there's the question around the role this technology is playing with publications in general. Like if now I can get an answer. For this tool, do I need to go all the way to the site to engage with it? And I think that, uh, that evolution was still being developed and built. I think we had the same thing with search to an extent where if I can get the answer for search, do I have to go all the way to the site and actually get the response in the site?

AI assessment note: “if now I can get an answer. For this tool, do I need to go”