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Why AI is disrupting traditional product management | Tomer Cohen (LinkedIn

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Video Source Why AI is disrupting traditional product management | Tomer Cohen (LinkedIn

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Tomer CohenWhen we look at the skills required to do your job, by 2030, it will change by 70%. So whether or not you're looking to change your job, your job is changing. In order to stay competitive, you actually have to go back to some first principles, go back to the drawing board and reimagine what it means to be building.

Lenny RachitskyYou're experimenting with a very different way of building product at LinkedIn that fully embraces what AI unlocks.

Tomer CohenWe call it the full stack builder model. The goal itself is to empower great builders to take their idea and to take it to market, regardless of their role and the stack and which team they're on. It's really fluid interaction between human and machine.

Lenny RachitskyThis feels like this could be a model for how a lot of companies operate and how product ends up being built in the future.

Tomer CohenChange management here is going to be a critical part, but it's not enough to give them the tools. You have to build the incentives programs, the motivation, the examples to how you do it. I see a lot of companies roll out their agents and just expecting companies to adopt. It doesn't work this way.

Lenny RachitskyThere's always been this question, is AI going to just make people that are not amazing, more amazing, or is it going to make amazing people even more amazing?

Tomer CohenTop talent has this tendency of continuously trying to get better at their craft. The key trait that I'm emphasizing for builders is...

Lenny RachitskyToday, my guest is Tomer Cohen, longtime chief product officer at LinkedIn, who is piloting a new way of building that I think will become a model for how companies operate in the future. It's called the Full Stack Builder Program, and essentially the idea is to enable anyone, no matter their function, to take products from idea to launch. They've scrapped their APM program and replaced it with an associate full stack builder program. They've introduced a new career path with the title Full Stack Builder that anyone from any function can become. And as you'll hear in the conversation, they've built a bunch of internal tools and agents and processes to basically build a human plus AI product team that can move really fast, adjust to change quickly, and do a lot more with a lot less. If you're looking for inspiration for how to rethink how your team operates and to lean into what AI is unlocking for teams and companies, this episode is for you.

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Tomer, thank you so much for being here and welcome to the podcast.

Tomer CohenThank you. It's great to be back.

Lenny RachitskyIt's great to have you back. I'm really excited to be chatting because you're experimenting with a very different way of building product at LinkedIn that fully embraces what AI unlocks, kind of leans into what is now possible, and to me, this feels like this could be a model for how a lot of companies operate and how product ends up being built in the future. There's a lot of product leaders that are talking about AI, what they can do. It feels like you're actually doing this in a really, really radical way, and so I'm excited to learn from you to hear about this for listeners to understand what you're seeing, what you've learned. Let me start with just why did you decide this was necessary? Why are you rethinking all of these things about how product has been built for a long time? AKA, why do people need to pay attention to what we're about to be talking about?

Tomer CohenIt really starts with kind of the basics. For me, technology has always been about empowerment. It's not about what it does for us. It's about what enables us to do. And now we have this amazing opportunity in my mind to make it about meritocracy, and I think it's an opportunity, but it's also a necessity right now, and I want to put this in context where we're entering this phase where the time constant of change is far greater than the time constant of response. Basically means that change is happening faster than we're able to respond to it. Now, LinkedIn has this unique view of the world of work. So we actually have some pretty, in my mind, mind-blowing stats to put this in perspective. When we look at the skills required to do your job, by 2030, which is literally four years from now, sounds a long time, but four years from now, it will change by 70%.

So whether or not you're looking to change your job, your job is changing. The only question is, do you keep it? And then we look at organizationally, the fastest growing jobs right now, the most in demand jobs in the market are growing by north of 70% from last year's fastest growing job. So there's a new kind of iteration of what you need as an organization to thrive. And then you apply that to building products and you realize that in order to stay competitive, you actually have to go back to some first principles, go back to the drawing board and reimagine what it means to be building. And what I love about this is when you think about the role of a builder, which the builder is at the heart of company, the goal is actually quite simple. The builder takes an ADN, she brings it to life. That's really the process, right?
And we all build those, let's call them best practices. You research the problem really well, you spec it out, you design it, you code it, you launch it, and you iterate. That's basically it. But what happens at many at scale companies, LinkedIn included and many other companies, over time that process became very complex very quickly. So what happened? We took every step and we expanded it to a lot of sub-steps. Researching, the problem became looking at for us 10 to 15 sources of information, obviously talking to customers about doing data pools, looking at feedback tickets in multiple sources, social media, interactions with customers. We probably have 10 to 15 sources of information we go for before we feel like we have research department really, really well.
Think about reviews for product. There is design reviews, privacy reviews, security reviews. I can go on and on and on. And each one of those substeps actually has a valid reason to exist. But when you add a whole thing together, you're like, "Oh my God. This is why it takes, to build a small feature, multiple teams, multiple code bases, multiple sprints just to get it out to launch," and not talk about iterating, which is actually where you seek success. You never see success in the launch itself. So really the work itself is not complex, but the process we made very complex. And when I was digging in, I found it doesn't end there because somebody has to do all those substeps, so what happened is you actually move from process complexity to organizational complexity as well.
And then you actually led to microspecialization. All those subsets are doing by somebody specific. So from one builder, we have multiple functions. Obviously we have engineering, product and design, and you can start questioning those lines. At least I am internally. And from there, we have a lot of subspecialties. It happens in every one of those functions, but imagine design. We have interaction design, animation design, content design, research. There's so many aspects to that. So they're all valid, but they all have people, and that entire process basically means a lot of... It's basically bloating. It's complexity. And then without noticing, you end up with this massively complex... We actually have this diagram that basically shows the process complexity, organizational complexity together.
And usually people are mind blown because they're working on one thing very specific, but when you zoom out, you have this overwhelming experience you're kind of thinking about. And now we have this real opportunity to collapse the stack backup, go back to craftsmanship, rethink the product development lifecycle, which is where the full stack builder model comes to life.

Lenny RachitskyWow. Okay. And there's so much here. We're going to be showing the visuals as you talk to help people see what you're explaining here. And all of this is very rational. If you have 15 sources of information, why not pull from it? Why miss out on that stuff? And what you're describing here is as you get more power and more specialized... It all makes sense rationally, but when you start to step back and look at this like, holy shit, it takes six months to launch one feature. I want to ask about the stat you shared. I think this is an incredibly powerful stat and you have very unique data here to tell you this sort of stuff. So you said that something like 70% of the skills that people will need in the future are going to change.

Tomer CohenTo do their current job.

Lenny RachitskyTo do their current job. And what is this looking at? Is this just based on historical data or how do you find that?

Tomer CohenYeah. To be fair, there was always a change, right? So it was never about just keep the skills you have today, but we've never seen such a dramatic part of your role today. So whether you are a marketer right now or a seller, a recruiter, an engineer. Engineering is where a lot of the investment is going in right now in terms of agents. Those jobs will change dramatically. I remember I said my role, my life as an engineer and even then it's changed materially after 10 years, and then the change we're seeing right now, just thinking about in four years, what did it take to actually engineer really, really well would be dramatically different, or to build software, to build an artifact of some sort. But it's true for almost every function. It's not equal. Some job like nurses will see less impact, but some jobs will see 90%, 95% impact.

Lenny RachitskyThere's also a stat that I don't think you mentioned here that I saw on the post when you first talked about this program is that 70% of today's fastest growing jobs were not even on the list of jobs a year ago.

Tomer CohenYeah. No, so this is the fastest growing job on the list were not there a year ago, and then many of them don't even exist a decade or two ago. There's actually some pretty amazing stats across the board.

Lenny RachitskyOkay. So let's talk about this program that you built. Tell us the name and then tell us the gist of what it is today and the vision of where you want it to be.

Tomer CohenYeah. So we call it the full stack builder model. And the goal, always start with the goal. The goal itself is to empower great builders to take their idea and to take it to market, regardless of their role and the stack and specifically which team they're on. And the idea ultimately is to be able for that builder is to develop experiences end to end, to combine skills and expertise across what was traditionally distinct domains to bring it all together. And it's not a sequence of steps. It's really a fluid interaction between human and machine. That's how the way I see it. And then when you look back at that product development life cycle from the idea, the insight all the way to launch, the key trait that I'm emphasizing for builders is where I want them to spend their time is where I think great builders should shine in.

So the idea of vision. Coming up with a compelling sense about the future. Empathy, super critical, right? Having a profound understanding of an unmet need. Communication is critical. And we see this a lot in job descriptions right now for almost every role, but ability for you to align and rally others around an idea. Creativity, which for me is about coming up with possibilities beyond the obvious. For example, I don't think AI yet is great at creativity. I think it's kind of, in many ways, brings back the things you might not know about, but it's not the kind of next level creativity, which I think still humans are much better at.
And then ultimately what I think is the most important trait for a builder is judgment. Some people call it test making, but it's making high quality decisions in what is complex ambiguous situations. Everything else, I'm working really hard to automate. Really, really hard. And then when you think about the outcome, it's not just about having more shots at the goal, which I think people go like, "Oh, the iteration speed is going to be very high." Yes, but what you're really doing to an organization of at scale organizations is they're a lot more nimble, a lot more adaptive, a lot more resilient. They can navigate the future. They can actually match the pace of change to the pace of response.
And an analogy I have in mind is kind of Navy SEALs. You come to training, they're all kind of learning, they're cross-trained, across multiple areas. What they specialize in is the mission and they operate in small pods and they're very nimble and you can assemble them very quickly. And I think that's going to be the organization that will win in the future.

Lenny RachitskyOkay. So the simple idea, if you're just to boil it down to a sentence, the idea here is there's a builder who goes through the entire product development process essentially on their own. They have an idea, they research, they do data, they prototype design ship. That's kind of like the vision of where this goes?

Tomer CohenYes, but it doesn't have to be on their own. It's not like... I still believe in teams.

Lenny RachitskyGot it. So smaller teams.

Tomer CohenJust smaller teams. Smaller teams and much more focused on the problem, the mission, per say, versus... Actually, one of the things we've done as an example, we started to do the idea of pods. We're no longer large teams. We assemble a team, ideally a full stack builders coming together and it's less about can I have an engineer design PM working together and trying to combine this trio looking at folks who can flex across and then they tackle something for a quarter or so and then we reassemble those two different pods. That's one example of an manifestation we're doing right now and seeing actually some great success in both in terms of velocity, but also in terms of that focus and nimbleness of that team.

Lenny RachitskyAnd it feels like the goal here, what you're trying to adjust and that broke as teams bloated as speed and adaptability and flexibility, because going back to your original point that change is happening so much more quickly now that companies that have been building in this traditional way just can't compete.

Tomer CohenYeah. It's not that you have to break the model. I think the model is broken. It's just this pace of change is helping us realize it.

Lenny RachitskyOkay. So then going back to the things that these builders still do versus what you want to automate. So the list you shared is they're responsible for the vision, empathy, communication, creativity, and judgment.

Tomer CohenYes. Yeah. And I would put a lot of the focus on the latter. I think if you ask me at the end of the day, what's the kind of most important trait? I would say it's that judgment, test making ability.

Lenny RachitskyAnd then in terms of what you're automating, what are some of the areas you've seen a lot of success in actually automating and where do you think this goes?

Tomer CohenYeah. So I think just to kind of break it to pieces, and I think this is... If you were a startup right now, in many ways you can start this way. There's no legacy code, there's no legacy structure you run. And in fact, a lot of the startups I talked to that are built AI natively, they're just working at full stack builders. That's the way they start. If you're at a company at a scale of ours and many others in the market, you're like, this is almost like a new production function and mindset that you have to do. And there's really three components that we're working on. One is platform. The second one is the tools and the agents. And lastly is the culture.

The platform one, this is the kind of level of investment you have to do before, before this actually starts, you start to see all the benefits accrue. But the platform for us as an example is rearchitecting all of our core platforms so AI can reason over it. So we're building kind of this composable UI components with server side that we actually build. We're basically building for AI to be ready to bring it in. So you can't just go and bring a third party tool and have it work on the LinkedIn stack. In fact, that's one of our biggest learnings. It never works. Never works. You have to bring it in and customize a lot of it, working almost in alpha mode with those companies to make it work internally.

Lenny RachitskySo this is essentially re-architecting your code base to work more efficiently with AI. Is that one way to think about it?

Tomer CohenYes. And in many ways, working with those companies to adjust something in their stack to work with our stack as well.

Lenny RachitskyWhen you say those companies, meaning the development agents like Cursors and and such?

Tomer CohenYes. Or Figma on design. Or you can think about design systems is another example of that. But you have to have that back and forth because they're not... In many ways, we haven't seen anybody be able to work off the shelf immediately on our code-based design systems and unique context we have.

Lenny RachitskyJust to follow that thread briefly, so there's Figma. That's interesting. So basically the way Figma exports and keeps your design system, that has to change to work better with AI is what I'm hearing.

Tomer CohenThey first need to know how to work with our design systems, which is something, in many ways a lot of those companies are working on. Same with coding. It doesn't work that you just bring it in and it just reasons over your code base really well. We tried. We are building that layer that basically allows it to do so, whether it's Copilot or Cursor, Windsurf and so on.

Lenny RachitskyGot it. Okay. Oh yeah, Copilot. Microsoft. I get it. I get it. Okay. Okay. So that's the platform. So that's an investment that you guys have to make to make AI effective at building and doing all these things.

Tomer CohenAnd then you have tools. So tools is where you really build the agents. I mentioned I want to automate everything outside of those five trades that we talked about, and then we're building the tools for that. And then for that, actually very similarly, I can't just bring a tool from the outside and work. So I'll give you an example. One of our biggest things is building a trust agent. Trust is really important for us at LinkedIn. There's a lot of unique vectors which trust plays at LinkedIn doesn't place it anywhere else. So we need to bring all of that know how and context and information base into that agent. So we ended up building our own trust agent at LinkedIn.

Lenny RachitskyAnd so what is this trust agent doing? Telling you when you're maybe exposing information that you shouldn't be?

Tomer CohenSo when you build a spec, you build an idea, you walk through the trust agent and it'll basically tell you what are your vulnerabilities, what harm vectors potentially you're introducing or will be introduced as a result of that. And I had our head of trust build it. So the head of craft for every area is building their own agent. As an example, we have one of our features for job seekers is called Open to Work. If you're looking for a job, you can put an open to work.

Lenny RachitskyYeah, a little green loading thing on the circle.

Tomer CohenExactly. And actually it's a great signal. I've seen some great success from it. People are helping each other. The community really thrives around helping each other. But at the same time, it introduces a trust vector for bad actors because they're open to work. People who are looking for a job are potentially more vulnerable to scams than other folks. So being able to think about how do we prevent all of those ahead of time. So we walked that spec from a couple of years ago through the trust agent. Not only was it able to find all the stuff we initiated at the beginning, but all the holes that we did not catch until later. So that's a great example of something that actually worked really well.

That's one. The other one is a growth agent, as an example. Again, LinkedIn has a very unique... Actually, we have an incredible growth team, growth process. We've kind of funneled all of our unique loops, our funnels, our tests of the past, everything into this growth agent, and now you can basically rock your respect for it, your idea for it. And it would not just allow you to do it better. It would actually critique how good is your idea. This is something you cannot bring off the shelf. It's very unique to LinkedIn. So we had to invest dramatically in it. And one team which is using it right now, which is almost... I wasn't thinking about it at the beginning, but our UXR team, our UER team, the user research team is usually using that growth agent to understand out of all the things that are basically surfacing for members, which one has the biggest growth opportunity to have the biggest impact? That was not in the cards when we thought about that idea, but teams are basically funneling those ideas into this one.
An example is our research agent. So research agent basically is trained on the personas of our members. You can think about a small business owner, a job seeker and so on. And it's using not just world knowledge, it's using all the research we've done in the past, all the support tickets coming in. So it's pretty good at understanding that persona at LinkedIn. So one examples we had is a team came out with a spec. They weren't aware we had the research agent yet. I asked the research agent for a small business owner, wanted to think about the marketing spec we had, and it critiqued it extremely well. Actually, in many ways shifted the direction of the team to focus on other integrations tools we can focus on, but it's very hard to have that visibility all to all that corpus of knowledge inside of the company.
That's another example. We have an analyst agent trained on all how you basically can query the entire LinkedIn graph, which is enormous. And instead of relying on your SQL queries or data science teams, you can use the analyst agent. All of those I would say are, I would call them still MVP+. The goal for us in the next couple of months to basically roll them out externally. Externally, I mean, internally at LinkedIn.

Lenny RachitskyNot as new product lines.

Tomer CohenExactly.

Lenny RachitskyOkay. So many questions. One is just how are you building this? Is there a platform you're using? What does it take to build an agent at LinkedIn? Is it all internal tools or is there third party use?

Tomer CohenIt's a great call. So I think we've been experimenting with a lot of tools. And I would say for a lot of those kind of knowledge corpus agents, we're using everything from Copilot Enterprise to ChatGPT Enterprise. By far though, the most important part was basically our own customization of it. That's been where we saw the biggest gains. Even building the orchestrator across those because you want the agents to start following to each other, the trust agent should work with the growth agent and go do a back and forth versus doing what more sequentially. So we've done a lot of work internally to make it happen. This is why I think it does require that level of investment.

And then in some cases, let's talk about the design agent that we're working with. We're working with multiple companies to try and understand which product works best for us. And interestingly enough, and this is another learning, different teams gravitate to different products. So that's something we'll have to resolve and think about how we do this really well, because ultimately we were trying to simplify the process as much as possible, but that was a big learning for us and which tools we use and how we basically integrate them in.

Lenny RachitskyGot it. So you might have an amazing Figma agent, but some teams want to use a different design tool.

Tomer CohenYeah. So we've kind of experimented with Figma and Subframe and Magic Patterns and so on, and we saw people gravitating depending on the function, their level of visibility, their know how of the tool before, they're gravitating to different tools. And ultimately, I don't want to have eight design agents in the company, so we have to converge into at least a few. And I think it's similar across many areas because the appeal of those, a lot of those agents are trying to solve similar end goal, but they're doing it very differently. And what you'll see that ultimately, I don't think there's going to be a winner takes all because the starting point of the customer or the user will dictate a lot how simple they are for that use case.

Lenny RachitskySuper interesting. The other interesting takeaway here is you're designing very specific agents that are one job to be done. Is that a very intentional decision? Did you try an agent that just is super intelligent on all these things?

Tomer CohenUltimately, they will do an orchestrator. We're going to really orchestrator across, but we did want to be able to rate and grade those agents really well on how they're doing. And I think there is a level of expertise. Now, we're kind of building this in a way where we'll be able to mask a lot of those. You might not know that there's a trust agent. You might have, we call this internally the product jammer agent that basically does your product jam, which is a process we do internally. You might just use the product jam engine, and that product jam agent will work with all the other agents. But now we're starting with that building blocks until we build the orchestrating layer across.

Lenny RachitskyAnother interesting takeaway from what you've been sharing is that so much of the work has gone into the beginning of the product development process, just like helping you craft the right requirements, clarify trust, and then here's product jam and here's the research we've done. And I imagine it's because coding has already been accelerated with all these IEE tools. Talk about just why that's maybe where most of the investment's gone and where you've seen the most impact so far.

Tomer CohenWell, 100% our coding investment has gone, started a while back, and those are fall into place. We have our coding agent. In fact, we've kind of staged it into two parts of it. There is the idea to design part, and then let's call it the code to launch part. The code to launch part has gotten a lot of attention and we're making some big inroads there. Everything from the coding agent to what we call the maintenance agent when you have a failed build, it will do it for you. In fact, I think we're close to 50% of all those builds being done by the maintenance agent and a QA agent.

Lenny RachitskyWow. So this is when a break builds instead of engineers hopping on the issues that an agent fix.

Tomer CohenYou can still go and finish your coffee before you have to go and redo the build again.

Lenny RachitskyExtremely cool.

Tomer CohenBut we haven't had much investment until we kind of launched this program in the idea to design area. And that's a material part of work. It's also where the quality a lot of the work comes from, at least before you start to go into the coding phase. The idea is to empower everybody. So if you're an engineer, you can basically use all those tools at the front of the process and be able to be a full stack builder.

Lenny RachitskyHow long did it take to get this kind of in place for you to actually form your first team to build these, the initial agents and some of this backend, redo the code base sort of thing?

Tomer CohenI announced this internally end of last year, we really kind of started working, but it was more setting up the teams and the processes internally. We had our first MVPs of those agents I think like four to five months after it was really trained, I would say. But really the work itself has been kind of couple of months of dedicated work. A lot of it has been getting all the corpus of data together, cleaning it up. And that's actually a good learning as well. It's not great to just give it access to your drive and say, "Reason all over this knowledge base." It actually does a very poor job understanding importance of the past and putting weights on stuff. You actually want to think about specifically what the context when do you want to give it to and what's the knowledge base that you want to have it focused on. So even cleaning up, let's call them gold examples or golden examples to learn from, has been one of the biggest learnings. Just reasoning over your entire knowledge base did not work.

Lenny RachitskyYeah, that makes sense. There may be just like a researcher with a strong opinion about something that you disagree with and it wouldn't know. It's like, oh, of course, this is data, this is fact.

Tomer CohenExactly. And then it doesn't always understand ties to original specs to success. You have to actually build... This is a really interesting way. When you think about how you bring those tools in, you can't just bring them in. You have to know what you feed them with. And what you feed them with is not just access. I see a lot to just focus on the connectivity and integration and it reminds me of the... This is almost like, this is actually more than 10 years ago when I was co-rebuilding the team, co-rebuilding the feed at LinkedIn and we started from scratch and I had to literally sit down and filter through examples of what is a good professional post on LinkedIn and what is not. And this was like weeks of work getting up that golden sample of examples, but it wasn't... The most important part was feeding at the right data, not all the data.

So it requires work. This is where I would say for many companies who are thinking about this phase, and I do a lot of sessions today with CPOs and COs on this process. You have to put this initial work to get the gains after. When I think about it, I think there's a takeaway there in generally with AI, even if you're learning it for the first time and so on, whether it's Cursor or whether it's design, if it's Figma or other tools or Lovable, you should be ready to invest those hours before you start seeing yourself pick up in velocity and quality, which will come up, but you have to invest that time.
What's the current state of the pilot? How large is it? How many teams are doing it? What kind of stuff have you shipped? Just give us a sense of today's world.

Tomer CohenYeah. I wouldn't say we are yet at a very high sample rate where it's kind of a high percentage of the organization, but we have a substantial part of the organization already using it to provide a lot of the feedback. We're seeing a lot of great examples. So the way I think about the benefits is a function of experimentation volume multiplied by quality. How good are those experiments divided by the time it takes to actually pull them out, like idea to launch. So on saving times, we're seeing, whether it's PMs, designers, engineers, saving hours of work a week right now, whether it's the analyst agent we talked about or the prototyping really quickly or the product jamming experience has been a big part of that. On the quality side, we're seeing insights discussions just be much, much better. And by the way, quality and time, sometimes they help each other because it's high quality, you don't have to spend as much time on something.

So we are seeing that applied in. And the volume, I wouldn't say we had a rate where I'm seeing a high percentage organization doing it yet, but this will come once we... We haven't GA'd this internally. That will come in the next couple of months once we have all the stuff in place. But we're seeing designers and PMs picking up bugs directly from Jira tickets, pushing them in, something we haven't seen before, and there's just an appetite for everybody to just join. So in fact, the biggest thing right now is everybody wants access. Everybody wants access to the tools to be able to do it together, and we just want to make sure it's good enough to make sure the whole organization can do it really well.

Lenny RachitskySo how is it that you're piling it? Is it some number of people have access to these agents and they just work the way they've worked with access to these tools? Or is there a team dedicated, this is the way you work now and this is it, and we'll see what happens.

Tomer CohenSo that's a great call. So basically we have a team building. It's the core team building the FSB track across all of R&D, FSB, full stack builder. And then there are pockets and pods of teams using it. So basically we are looking at specific areas that we're basically giving it to. The condition there is they give feedback. As a response for that, they make the tool better, so it's not just access. We want people who will use it. So one of your early adopters would be the ones who help up the product really well. So we're doing this in a pod model right now.

Lenny RachitskySo it's like a pod within a larger team, like a designer, PM, engineer kind of group within... Is there an example? You have a part of LinkedIn that's trying this out?

Tomer CohenYeah. So if I think about some of our teams, whether it's... Actually, we just launched Semantic People Search and the Semantic Job Search as well. That team was using part of those tools to actually help build it. So that team actually, this was PMs building their own dashboards with those tools without waiting for design resources to come in. Then we have a design team who is now... This started really from the manager rolling this out. And in many ways, what I tell this team is, "Don't wait for the official GA. Start doing it. Start leaning in." We're seeing designers of that team starting to push PRs, which never happened before. And now other teams, they want to do this as well. So it's starting with this kind of grassroots experience. I would say the places have been very formal. I would say the beginning has been the top.

The product executive teams, basically we move from functional leaders, design, PM, BD, and so on to product areas leaders, and they basically rock across the stack and they also go for a 360 with all of those functions to see if they're really able to do a full stack building experience. Then we're also launching at the junior side a new program called the Associate Product Builder Program, where basically we used to have our APM program, which this is about it's ending this year. And then starting January, we're going to start having our APB program and they're going to come into LinkedIn. We're going to teach them how to code, design and PM at LinkedIn. They're going to go through a pretty rigorous training process, and then they're going to join those pods, and gradually we're going to grow that program to be a material part of LinkedIn as well.

Lenny RachitskyWow. So this might be the future of the APM program is this full stack builder APM-ish program.

Tomer CohenIn many ways, we've built some pretty amazing... I'm really excited for that group. I wish I could join it. But we build amazing training for them. And in many ways, we're going to use that training to think about how we roll it across the organization. We're kind of using the lens of you have great technical skills, but you're not an engineer at a company yet, or you have great design taste, but you haven't designed at scale in company yet, and we're going to teach you how to do it at LinkedIn, but the training we're going to use a lot to extend across the company as well.

Lenny RachitskyOkay. So you have these programs, these pilots and these pods, and you said what you're looking at to see if this is something you roll out is experiment velocity times quality times time.

Tomer CohenDivided by time.

Lenny RachitskyDivided by time. Okay.

Tomer CohenYeah.

Lenny RachitskyGot it. And I guess I know it's early, but just you said you're seeing that it's saving teams a few hours a week at this point, something like that?

Tomer CohenYeah. And I think the feedback has been the most important part. Right? The way to think about this is just like you build a product. So we're building this product internally and you want to experiment with some kind of early adopters who will give you feedback, and the feedback has been amazing. In fact, our top talent are the ones who are using this the most at LinkedIn. And the feedback from them has been incredible in terms because they're also willing to spend the time and give the feedback as well. And the response from them has been incredible in terms of like the quality of their output, the time they're spending on this to get the value back, their desire to be part of this and actually scale this and make this even better. So that's where a lot of the excitement has been from how they're using it and the quality we've seen there. I would say in six months or so, we'll be able to see a lot more of the organization use it and you'll start seeing those top line numbers will build as well.

Lenny RachitskyThat is a really interesting insight that the top performers are finding the most success, because there's always been this question, is AI going to just make people that are not amazing, more amazing, or is it going to make amazing people even more amazing? And it sounds like it's likely the latter.

Tomer CohenYes. And in many ways, it's surprising, it's not surprising. I've seen this also when we were... It's surprising because you want everybody else to be part of this and lean in. I think top talent has this tendency of continuously trying to get better at their craft and this innate need to be at the cutting edge of how you build, and I think we're seeing this here as well. This is why I had this phrase I say with the team that if we build all those tools, will they use it? And I know right now the answer is no. It's not enough to give them the tools to use it. You have to build the incentives programs, the motivation, the examples to how you do it. They need to see other people being successful as well.

And I've seen this also when we're shifting LinkedIn from a desktop company into a mobile company. It was a very similar process. It's very hard. Change management here is going to be a critical part. I think I see a lot of companies roll out their agents and just expecting companies to adopt. It doesn't work this way. Some will adopt. That tends to be your cutting edge 5% of talent that just wants new tools and they have a bias for change. But the vast majority needs to work for change management in how they do it, and that requires being a lot more thoughtful about the cultural aspect of it, which is by far from me the biggest and most important thing to do.

Lenny RachitskyYeah. I want to spend time there. And it makes a lot of sense why people don't spend time here because they have so much to do. They got to ship things. Their days are already busy. You have to now carve out time to learn this new tool that'll not pay off for a while. So I get why people are like, "Okay, okay, I'll get there. I'll use it someday," but they don't. This idea of culture, when I saw you share this initially, this is the third piece of making this successful. So there's the platform of getting the code base ready for people for AI to work with. Then there's the tool, like the agents you've talked about, and then there's the culture. Is there more there that you can share of just what has actually worked in helping get people on board? One thing I heard is creating a little bit of FOMO of like, okay, only a few people can use this and you have to sign up to get access. What's worked in getting people to get on board?

Tomer CohenYeah. I think this is where I emphasize to people that getting everything done, the platforms, the tools is not going to be sufficient. It's a prerequisite for this to work, but not sufficient for this to work because it really requires you to invest a lot in the cultural aspects of how do you get people to lean into this one. And this one might feel slow at first, but I've seen this before with our transformation of thinking from desktop to mobile. And once it picks up, it actually maintains very high velocity. One, people are really incentivized by how you define expectations for them. So to think about what is the expectation of somebody in the role, whatever-

Lenny RachitskySo like changing performance review sort of things.

Tomer CohenVery much so. So everything from how you hire to calibration and evaluation. And one thing I want to see there early is this kind of AI agency and fluency. Like I mentioned, the tools are there. The question is, would you use them? Because the tools will be good enough, but not great at the beginning. That's the classic thing of every good MVP tool. They're good enough, but they're not great. And then you kind of want to build that agency to make the tool better. We're in this kind of notion of we're going to make this better for LinkedIn together. Two is piloting success inside of your organization. That's the pod model where you're showing that not only this could work, it's actually having success. So we have even our partnerships team, our BD team, being able to go instead of relying on waiting for an engineer to help build the developer portal and build the connectors there.

Literally one of our head of partnerships just went and did it himself. Didn't even delegate to his team. And their goal is to say like, "Hey, I can do it. You can do it as well." Those examples are really, really powerful. I talked about the associate product builder program where we are going to be very focused on training. I think that will send a really strong message across the organization. People will see this talent and what they can do, and I think that will create that movement. But celebrating wins in all hands, highlighting people and showing those examples. One example we've seen recently, people really looked at it in a surprise lens, but then it kind of, I think, really opened up a lens for them. We had somebody in our user research team. We had an opening for a PM on the growth team, and that role was open for a while, and she said that, "I think I can do it."
And she used all these tools. This is a user researcher becoming a growth PM, not usually the career path you see, but she was excited about the area. She used all those tools, and she's now a growth PM on the team. And really, you can start thinking about her more as a full stack builder ultimately. But seeing those openings and then highlighting those two people, actually people who are doing this have been a great example of it. And then just making sure that those tools are accessible. People can provide feedback, you share a lot, has been an incredible part of this. It's not enough to be top-down directive that this is how we want to work. People want to feel like there are success stories. They feel like it's worth their time. It feels it's a movement they want to be part of, and then ultimately they can see successes in how they do it.

Lenny RachitskyI love this kind of comparison to the shift to mobile. We all went through that and there's all these stories of companies requiring you to show mobile mocks. That's the only way we're going to operate. Now everything you have to ship has to be on mobile, and it's interesting how similar this is to them, to that experience. And so a few things you just shared here just to kind of summarize some of the things that have worked for you. Showing wins, celebrating wins, showing people what other folks are doing with AI tools, creating a program that people enroll into and make it a little bit exclusive. This performance review piece is really interesting because that really will change people's behaviors. Here's how we get promoted. Have you actually already made that change to the PM? I guess it's every track, I imagine, not just product management. Have you already made that change or is it kind of like a work in progress?

Tomer CohenSo there was two aspects to it. Once I moved my team, my directs, we did 360 for them. So their 360 was, if you came from PM, you had the designers on your team rate you. And so that had its own, and then we shared those with them, and that had its own kind of motivation. But then we broadly took it across. So when we hire right now, we look for those. And then this upcoming cycle, we do a bi-annual. That's going to be part of the performance evaluation piece and we announce it to everybody. And for what, it's where people are excited to show. And they're excited to know how they're going to be... It's always about, like, "I want to know how I'm being rated or evaluated." So just being able to show those examples has been a big part of it.

The other thing I would say, it takes time for this program and its formality to roll out across the entire organization, and I was intentionally not trying to be quick at rolling this out to everybody because I think that just dilutes the value of it really quickly because it's not about... I could care less about your title. I care about how you work. So calling you a full stack builder is not what I'm looking for. Changing your mindset to a full stack mindset is what I'm looking for. You're thinking you can do the whole thing. You're looking at those tools and looking at how to do it.
So one of the things I've said is if you're looking for a formal reorg or declaration to start building differently, you're waiting too long. Look, my biggest thing is here's a permission for me to just not wait and just go. So whether or not you have the right tools or not, go build the tool, use a tool from the outside, bring it in, show those examples. In many ways, prove that you are a full stack builder in mindset before anything else come to mind. And that just naturally will happen, and that's also where we've seen some of our best talent just goes and leans a lot into.

Lenny RachitskyI love that. I was going to actually mention that quote. Someone you shared, you work with told me exactly that quote you just shared, so I'm glad you brought it up of just if you're waiting for a reorg, you're not thinking about it the right way. How do you encourage people to actually play with these tools on their own? Are you just like, "Go take a few days to play with AI?" Is it just try it? Or is there anything formal you've seen of just getting people to more try this on their own without joining this program?

Tomer CohenA lot of the tools we've made, we've been sharing them regularly. A few of my all hands have been all about how to use those tools. But then at the same time, we're kind of inviting, have you found a new tool that works really well for you? Share it, show it. Again, it could be Slack, could be Messages, Teams and so on, how you do it. But the idea is really to start getting that investment in how things work. Actually, I think in general, you can feel overwhelmed by tools right now, by recipes and how to do things like what's your prompt and what's my prompt. But really it's finding something that kind of works really well, that can gravitate around and really invest in that's been those areas. But I think we've had this invitation to go and explore and go and bring in stuff that you think are great. And in many ways, bring others along on the journey. It's one good way to make the influence much bigger than a few folks who are doing really well with this.

Lenny RachitskyAre there any surprises on the negative side that have come out of this, of PRD is just feeling like AI driven, people slowing down unexpectedly? Is there anything that surprised you of just like, "Okay, this is actually not great"?

Tomer CohenYeah, we mentioned a few of them. I was hoping for some tools to work off the shelf really well. It was never the case because we had to invest quite a lot.

Lenny RachitskyNever the case.

Tomer CohenNever the case. We had to invest quite a lot. And again, part of it is we just have a lot of legacy information and code based and knowledge and designs and so on. So a lot of the companies we work with are seeing this as a great growth opportunity for them as well to invest, but I do think it's a big area of investment as well. We talked about not just giving access to all of your context which we started with, and we were like, "Oh, here's access to all the drive, all information," failed miserably and hallucinates like crazy." People gravitating towards different tools, like our goal was to converge on tools, but that was pretty hard.

And then I think in terms of quality, we've just seen better quality, but I think it's because, again, where we are in the stage is still the early adopters and they're doing a few iterations in terms of how to do it. But I would say the tooling adoption is hard. And then I think for some people, this is important for me to kind of state, some people do not want to be full-stack builders, and that's completely okay. Some people see themselves in specialization, and I think specialization has a place and a role. So I didn't want the message to be across the organization I expect everybody to be a full-stack builder. I do not. I think there are system builders that empower full-stack builders, and then you have people who are specialized. But I don't think we need as many specialized people as we did in the past.

Lenny RachitskyI didn't actually realize this until just now. So is this their title now instead of product manager engineer, they're full stack builder?

Tomer CohenWe have a full stack builder title formally inside the organization, and we are gradually putting people in that bucket.

Lenny RachitskySo there's a whole career ladder that's forming. There's a whole... Okay. That's a bigger deal than I even thought. So where are you finding these folks mostly coming from, like product, engineering, design? I imagine it's a mix, but just is there a most common trend?

Tomer CohenIt's a mix. People listening, I would just think about just go over your org and imagine who can do it, who can right now flex across those functions, whether it is engineering, design, product, even BD, and what you'll find is there's already quite a few that can flex across.

Lenny RachitskyInteresting. Are there any functions you think are especially successful at this? Not to play any favorites, but I don't know. Are you finding like, okay? Or you could also not highlight any specific.

Tomer CohenNo, I think it's a mental model of how you do it. I think if I were to play what's the hardest craft to potentially learn, I think design has a lot more work to get the design agents to be really, really good. So I think designers have a little bit of a leg up in terms of others learning their craft than the vice versa. But I honestly think it's a mindset. I've seen designers code, I've seen PMs kind of design and do well. And this is why I think when you kind of step back and you think about people in your organization and who can flex, I think you'll see them show up in many areas. And what I think you'll find there is they have the agency, they're leaning into new things, they have the fluency, like they're already building new experiences and they have that growth mindset that they just want to get better, so it doesn't matter what they learn at school or what label somebody put in them when they join the company.

Lenny RachitskyWhat I love about a lot of this is it's the easiest time to transition between different product roles than it's ever been. Design's moving to PM, and sure, or just moving to this new role, it makes it so much easier to, like you said, that researcher became a growth PM.

Tomer CohenAnd this is probably my biggest advice slash motivation I give to the team because what I tell them is ultimately... By the way, this is for me as well. I think about it the same way. The incentives for you are so aligned with your organization of what we're asking for, right? Because we need you to change. We want to be a more agile, adaptive, resilient organization that can deal with the pace of change, but you want as well for your own career. You want to be at the cutting edge of how you build. So the incentives are really aligned between what you need for your own career and what the organization needs you to do. So there's that permission to go and do it for me is ideally kind of a tailwind in what they want to do more than anything else.

Lenny RachitskyMaybe a last question for people that are inspired and like, "Okay, this is what we need to be doing," any just tips for someone starting down this road to be successful at trying something like this at their company?

Tomer CohenI would say I would start with the notion of how do you want to bring this just structure. I would think about the platform you need to build, the tools you want to bring, and then I would spend a lot of time on the culture. Platform and tools I think would be, again, a prerequisite, but not sufficient, and the cultural aspect is really important. I would think a lot about how you bring people along. So for one of the learnings we had that probably able to do it differently right now, if I were to redo this program was, for a while I was working very closely with my core team on it, the core kind of full stack building team that were in charge of building all this material, but the organization was always asking questions. "What's going on? Who is doing it? What are the tools?" And in retrospect, we could have done a lot more in the flow to just show them and get them to already use early tools or be aware of it versus doing a small team on the side.

So it's okay to start with a small team. I think it's really important. But at the same time, just making sure there's visibility across the whole thing is really powerful. Being patient and being willing to invest. I always give this example of, we always give this example of like, "Oh, look at this startup. They built this in a week." Yes, you can build lifestyle in a week right now if you start from scratch. It's actually not hard. But when you are trying to transform a large organization, you want to have this impatient about the goal and you have to have a high ambition, but being very thoughtful and patient about how you bring it to life and the key things you have to invest in. If you don't invest in your platform, I just don't see how this could be a successful outcome. If you don't invest in customizing the tools for you, then you're just going to get vanilla generic agents from the outside.
So being aware of the investment and making sure you actually allocate resource to it, this is kind of the classic, be willing to invest upfront so you can reap the benefit after, versus saying, "Hey, why am I not seeing us moving into 2X the productivity in a week?" That's not going to be this way. You can see it with some people, but starting to collect those examples and starting to really think about the transformation is really key.

Lenny RachitskyThis is so incredibly cool. I know that a lot of CPOs and heads of product and all kinds of leaders are reaching out to you trying to figure out what you've learned how to do this. So I love that we went deep on all these things. Just final question, is there anything else that we haven't shared that you think might be helpful for listeners to hear or maybe just to double down on before we get to our very exciting lightning round?

Tomer CohenWhether you're in an organization, you're waiting for your leader to roll this out or you're a leader trying to roll this out, I would not wait. The first thing I've done, which I thought in retrospect was very hopeful is I did announce this upfront we are going to this mode. We're starting in pockets, we're starting in pods, we're building the tools, but this is the mountain we're going to go after, and in many ways, we're going to make it great. I also announced that this is not just an end state, it's a kind of continuous progress. There's no state we're going to get to as much as continuously just trying to be better. And in many ways, to compete, you just want to be better than others in how you build because the version of building will completely just transform itself every few years or so.

So do not wait. Really focus on the progress you're making, over communicate with your team, not just the vision, but also the progress you're making, almost like holding yourself responsible. If you're a leader, give yourself KPIs you share with your own teams or OKRs. And if you're inside of the organization, and I would say whether or not or not your CPO or your CEO is announcing this type of program, go do it or join an organization that does it so you can be at the cutting edge of how you build in the future.

Lenny RachitskyTomer, with that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready?

Tomer CohenI'm ready.

Lenny RachitskyFirst question, what are two or three books you find yourself recommending most to other people?

Tomer CohenI love to give trios of books that I really like. So my current trio is, they're very diverse in topics, so apologies if it's not falling all into tech. But the first one is called Why Nations Fail. It's a book I read a decade ago even more and the authors of it just won the Nobel Prize last year. And it basically talks about why does some nations succeed and some fail? And it's not the usual explanations we go for, which is, oh, it's culture, it's natural resources, it's the kind of religion. A lot of those tends to be the kind of immediate excuses people have. It kind of falls into two camps. Are there extractive or inclusive institutions? Can people participate broadly and opportunities shared or there are institutions that basically are supposed to be attracting from many and give to some.

So it's just an incredible way to just think about how you build a nation. And for us at LinkedIn, we think a lot about the idea of opportunities, so how you build a product as well. And it's just a good way to move away from easy explanations into what really makes a country really successful as well. Second book, it's called Outlive. It's really about the idea, it's kind of like the author, Peter Attia talks about the idea of medicine 3.0, which is really the notion of building personalized medicine, which I think in the world of AI will become incredible in the future. But it's all those, let's call those categories that you should think about for your life so you can just optimize your health as much as possible and goes for everything through fitness to diet to the biggest health factors you should think about. But it's a great long book. Then lastly-

Lenny RachitskyThe one in my bookshelf behind me.

Tomer CohenThere you go.

Lenny RachitskyIt's up top. You can't actually see it, I think.

Tomer CohenAnd then lastly, it's a book that also came out many years ago, but it's called The Beginning of Infinity, which I really like, by Deutsche. It wasn't an easy read for me, but I love the idea. In fact, especially in products, I love the idea of cause and effect, like really finding great explanations for why things happen and then building on top of that your next iterations. And this book really pushes on the idea of explanations that only once we have a clear understanding of what things happens, then we can have breakthroughs on top of that. But until we get to a point of clear scientific breakthroughs, we are not going to make significant progress. But when you do that, it's really almost like infinite progress you can make on top of that.

Lenny RachitskyNaval's always talking about that last book. I think I bought it and it was just hard reading this.

Tomer CohenIt's not an easy read, at least for me. It wasn't an easy read, but it's a very powerful read.

Lenny RachitskyAwesome. Is there a favorite recent movie or TV show you really enjoyed?

Tomer CohenCan I do a podcast?

Lenny RachitskyAbsolutely.

Tomer CohenSo there's a podcast in, it's in Hebrew, it's called One Song, and it takes a song that generally is ideally popular and then goes really deep on the origin and the history of the song, and I love it. I love music and just dissects songs so well. It does a great job also in bringing to life the story behind it. So for me, it just goes back to you thought the song was about something, but then it goes really deep into the actors behind the song, and sometimes it's the words chosen or it's how the lyrics match the music itself, and I just really enjoy that one.

Lenny RachitskyThere's a podcast called Song Exploder, I believe, that is a similar concept that's not in Hebrew, in English, that I'll point people to if you love that one.

Tomer CohenThat's awesome.

Lenny RachitskyIs there a product you've recently discovered that you really love? Could be an app, could be some clothing, could be a kitchen gadget, type gadget.

Tomer CohenCan it can be a product I want to have, which I think is actually really easy to do?

Lenny RachitskyI love that. This is a product thinking 101 and just the vision of what you want to see.

Tomer CohenSo in my car right now, there's Alexa built-in, which is great because the kids can ask for songs all day long and it's a whole show inside of the car. But one of my favorite things to do when this has been doing it for well over two years is I go in and I go into voice mode.

Lenny RachitskyChatGPT.

Tomer CohenYeah, ChatGPT, and then just have a conversation, and that's just friction. I would love to have on my steering wheel a button that invokes my AI friend that can sit next to me in the passenger seat, and I just think that would be such a... I actually think it would rides for people. Just that movement, that's just like elimination of friction will transform the experience for me.

Lenny RachitskyOn that note, I recently discovered Teslas actually do this now. If you hold the right wheel, Grok appears and you could talk to Grok. So it's here. The AI has arrived. Yeah. I just did it by accident and then it's, "Okay, cool."

Tomer CohenGreat. So for me, if anybody from Rivian is listening, please bring this in the car.

Lenny RachitskyRivian's falling behind. Yeah. And you have to use Grok. It'd be cool if you could switch to different AIs because it has a personality. Just give me information. I don't need you to laugh and give me jokes.

Tomer CohenDid you need to spend some time with it before or did it have any memory from... Did you bring any memory into it?

Lenny RachitskyThere's a logged out version and then you could just log in and it connects to your account. Yeah, it's extremely cool. No one's talking about it. It's crazy because I don't know if they launched it fully, but it just appeared.

Tomer CohenDo you talk in the car a lot to it?

Lenny RachitskyI don't use it that much, to be honest, but I should. My wife just doesn't love Grok. I think the brand of Grok is a specific brand. And so she's like, "Don't talk to Grok in here with me."

Tomer CohenI love voice mode, so I use it all the time.

Lenny RachitskyYeah, I love voice mode too. It just interrupts too often. That's the issue there, right? It's just it stops.

Tomer CohenBy the way, you can set it up. You can basically say like, "Hey, just let me finish."

Lenny RachitskyI now know that. I'm learning so much. Okay. Two more questions. Do you have a life motto that you often find useful in work or in life?

Tomer CohenI think last time I talked about it, I most associated here with, I might be wrong, but I'm not confused, although I don't say it as much anymore. But I think the one I love, growth mindset is a second religions for us at home. And one thing I love about, there's a phrase there that is becoming is better than being, which I think ties into the FSB mode a little bit, which is you're always in progress mode, iteration mode. It's not about reaching a state. It's about the journey, the process. That's what you should fall in love with. It's about continuously growing and evolving without the negativity of it or there's no sense of FOMO there. It's just this continuous thing. If I look back a year from now and I look back, how much did I grow? How much do I know? What skills to do that again? Where are I becoming better? Do I feel like Tomer version 2026 versus 2025? What's the delta there? And I kind of love that as a way of thinking.

Lenny RachitskyA great segue to our final question. By the time this episode comes out, it won't be a secret that you're leaving LinkedIn after 14 years. Legendary run. You joined way before the acquisition, you helped them integrate. Just like the way LinkedIn was perceived 14 years ago is so radically different from the way it is today. It's actually really fun and interesting to be there versus how people for a long time felt about LinkedIn. So I guess the question just how you feeling and what's next? I imagine you're going to get a lot of calls from a lot of people, but what are you planning?

Tomer CohenYeah, so I feel proud. It's been an incredible ride at LinkedIn. The way I've got to know about LinkedIn deeply the very first time was when I moved to the Valley and I went to a lecture at Stanford about social networks in 2008 and Reid was there and he talked about the power of being a professional communities online, and I was very nerdy about it and thought it was incredible vision, had no plans to join and actually started my own company after. But as luck would have it, found myself joining a few years after and just thought the mission was incredible. So in many ways it aligned with my purpose and just was an incredible ride to be here.

And I also feel very grateful. I shared this with the company recently. I was starting to take learnings from my experiences here. A lot of it was from tough situations. We had a lot of tough situations at LinkedIn and hard calls and late nights, but you learn so much from those and I'm just incredibly grateful. And I'm excited. I'm excited. I have a bias for change. I have a bias for kind of positioning myself in a place where I can learn the most and learn a lot. And it's an incredible time to build, so I'm just excited to be thinking of new problem sets and new areas where I can go deep on and invest the next decade in.

Lenny RachitskyI think it's going to take a long time for you to not feel like you're working on LinkedIn and to forget about all the things that you have been worrying about for so many years.

Tomer CohenAfter you build something for such a long time, and I think you and I talked about it at one point, that I think one of the best traits for a builder is to become very passionate with what they're building. Really care. Not about the job. It's really care about the product. When you feel the pain when somebody complains and you kind of have this continuous discontent, and it's like for me, it's the notion of raising a baby. So yeah, it's hard. It will be hard. I will always think of LinkedIn as one of the babies I helped grow.

Lenny RachitskyWell, I'm excited to have you back someday when you figure out what you want to do next and or start whatever you're doing. I love that this was an excuse to get to know you. Tomer, thank you so much for being here.

Tomer CohenIt was great to be here. Thanks, Lenny.

Lenny RachitskyBye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.

English Original transcript

Tomer CohenWhen we look at the skills required to do your job, by 2030, it will change by 70%. So whether or not you're looking to change your job, your job is changing. In order to stay competitive, you actually have to go back to some first principles, go back to the drawing board and reimagine what it means to be building.

Lenny RachitskyYou're experimenting with a very different way of building product at LinkedIn that fully embraces what AI unlocks.

Tomer CohenWe call it the full stack builder model. The goal itself is to empower great builders to take their idea and to take it to market, regardless of their role and the stack and which team they're on. It's really fluid interaction between human and machine.

Lenny RachitskyThis feels like this could be a model for how a lot of companies operate and how product ends up being built in the future.

Tomer CohenChange management here is going to be a critical part, but it's not enough to give them the tools. You have to build the incentives programs, the motivation, the examples to how you do it. I see a lot of companies roll out their agents and just expecting companies to adopt. It doesn't work this way.

Lenny RachitskyThere's always been this question, is AI going to just make people that are not amazing, more amazing, or is it going to make amazing people even more amazing?

Tomer CohenTop talent has this tendency of continuously trying to get better at their craft. The key trait that I'm emphasizing for builders is...

Lenny RachitskyToday, my guest is Tomer Cohen, longtime chief product officer at LinkedIn, who is piloting a new way of building that I think will become a model for how companies operate in the future. It's called the Full Stack Builder Program, and essentially the idea is to enable anyone, no matter their function, to take products from idea to launch. They've scrapped their APM program and replaced it with an associate full stack builder program. They've introduced a new career path with the title Full Stack Builder that anyone from any function can become. And as you'll hear in the conversation, they've built a bunch of internal tools and agents and processes to basically build a human plus AI product team that can move really fast, adjust to change quickly, and do a lot more with a lot less. If you're looking for inspiration for how to rethink how your team operates and to lean into what AI is unlocking for teams and companies, this episode is for you.

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Tomer, thank you so much for being here and welcome to the podcast.

Tomer CohenThank you. It's great to be back.

Lenny RachitskyIt's great to have you back. I'm really excited to be chatting because you're experimenting with a very different way of building product at LinkedIn that fully embraces what AI unlocks, kind of leans into what is now possible, and to me, this feels like this could be a model for how a lot of companies operate and how product ends up being built in the future. There's a lot of product leaders that are talking about AI, what they can do. It feels like you're actually doing this in a really, really radical way, and so I'm excited to learn from you to hear about this for listeners to understand what you're seeing, what you've learned. Let me start with just why did you decide this was necessary? Why are you rethinking all of these things about how product has been built for a long time? AKA, why do people need to pay attention to what we're about to be talking about?

Tomer CohenIt really starts with kind of the basics. For me, technology has always been about empowerment. It's not about what it does for us. It's about what enables us to do. And now we have this amazing opportunity in my mind to make it about meritocracy, and I think it's an opportunity, but it's also a necessity right now, and I want to put this in context where we're entering this phase where the time constant of change is far greater than the time constant of response. Basically means that change is happening faster than we're able to respond to it. Now, LinkedIn has this unique view of the world of work. So we actually have some pretty, in my mind, mind-blowing stats to put this in perspective. When we look at the skills required to do your job, by 2030, which is literally four years from now, sounds a long time, but four years from now, it will change by 70%.

So whether or not you're looking to change your job, your job is changing. The only question is, do you keep it? And then we look at organizationally, the fastest growing jobs right now, the most in demand jobs in the market are growing by north of 70% from last year's fastest growing job. So there's a new kind of iteration of what you need as an organization to thrive. And then you apply that to building products and you realize that in order to stay competitive, you actually have to go back to some first principles, go back to the drawing board and reimagine what it means to be building. And what I love about this is when you think about the role of a builder, which the builder is at the heart of company, the goal is actually quite simple. The builder takes an ADN, she brings it to life. That's really the process, right?
And we all build those, let's call them best practices. You research the problem really well, you spec it out, you design it, you code it, you launch it, and you iterate. That's basically it. But what happens at many at scale companies, LinkedIn included and many other companies, over time that process became very complex very quickly. So what happened? We took every step and we expanded it to a lot of sub-steps. Researching, the problem became looking at for us 10 to 15 sources of information, obviously talking to customers about doing data pools, looking at feedback tickets in multiple sources, social media, interactions with customers. We probably have 10 to 15 sources of information we go for before we feel like we have research department really, really well.
Think about reviews for product. There is design reviews, privacy reviews, security reviews. I can go on and on and on. And each one of those substeps actually has a valid reason to exist. But when you add a whole thing together, you're like, "Oh my God. This is why it takes, to build a small feature, multiple teams, multiple code bases, multiple sprints just to get it out to launch," and not talk about iterating, which is actually where you seek success. You never see success in the launch itself. So really the work itself is not complex, but the process we made very complex. And when I was digging in, I found it doesn't end there because somebody has to do all those substeps, so what happened is you actually move from process complexity to organizational complexity as well.
And then you actually led to microspecialization. All those subsets are doing by somebody specific. So from one builder, we have multiple functions. Obviously we have engineering, product and design, and you can start questioning those lines. At least I am internally. And from there, we have a lot of subspecialties. It happens in every one of those functions, but imagine design. We have interaction design, animation design, content design, research. There's so many aspects to that. So they're all valid, but they all have people, and that entire process basically means a lot of... It's basically bloating. It's complexity. And then without noticing, you end up with this massively complex... We actually have this diagram that basically shows the process complexity, organizational complexity together.
And usually people are mind blown because they're working on one thing very specific, but when you zoom out, you have this overwhelming experience you're kind of thinking about. And now we have this real opportunity to collapse the stack backup, go back to craftsmanship, rethink the product development lifecycle, which is where the full stack builder model comes to life.

Lenny RachitskyWow. Okay. And there's so much here. We're going to be showing the visuals as you talk to help people see what you're explaining here. And all of this is very rational. If you have 15 sources of information, why not pull from it? Why miss out on that stuff? And what you're describing here is as you get more power and more specialized... It all makes sense rationally, but when you start to step back and look at this like, holy shit, it takes six months to launch one feature. I want to ask about the stat you shared. I think this is an incredibly powerful stat and you have very unique data here to tell you this sort of stuff. So you said that something like 70% of the skills that people will need in the future are going to change.

Tomer CohenTo do their current job.

Lenny RachitskyTo do their current job. And what is this looking at? Is this just based on historical data or how do you find that?

Tomer CohenYeah. To be fair, there was always a change, right? So it was never about just keep the skills you have today, but we've never seen such a dramatic part of your role today. So whether you are a marketer right now or a seller, a recruiter, an engineer. Engineering is where a lot of the investment is going in right now in terms of agents. Those jobs will change dramatically. I remember I said my role, my life as an engineer and even then it's changed materially after 10 years, and then the change we're seeing right now, just thinking about in four years, what did it take to actually engineer really, really well would be dramatically different, or to build software, to build an artifact of some sort. But it's true for almost every function. It's not equal. Some job like nurses will see less impact, but some jobs will see 90%, 95% impact.

Lenny RachitskyThere's also a stat that I don't think you mentioned here that I saw on the post when you first talked about this program is that 70% of today's fastest growing jobs were not even on the list of jobs a year ago.

Tomer CohenYeah. No, so this is the fastest growing job on the list were not there a year ago, and then many of them don't even exist a decade or two ago. There's actually some pretty amazing stats across the board.

Lenny RachitskyOkay. So let's talk about this program that you built. Tell us the name and then tell us the gist of what it is today and the vision of where you want it to be.

Tomer CohenYeah. So we call it the full stack builder model. And the goal, always start with the goal. The goal itself is to empower great builders to take their idea and to take it to market, regardless of their role and the stack and specifically which team they're on. And the idea ultimately is to be able for that builder is to develop experiences end to end, to combine skills and expertise across what was traditionally distinct domains to bring it all together. And it's not a sequence of steps. It's really a fluid interaction between human and machine. That's how the way I see it. And then when you look back at that product development life cycle from the idea, the insight all the way to launch, the key trait that I'm emphasizing for builders is where I want them to spend their time is where I think great builders should shine in.

So the idea of vision. Coming up with a compelling sense about the future. Empathy, super critical, right? Having a profound understanding of an unmet need. Communication is critical. And we see this a lot in job descriptions right now for almost every role, but ability for you to align and rally others around an idea. Creativity, which for me is about coming up with possibilities beyond the obvious. For example, I don't think AI yet is great at creativity. I think it's kind of, in many ways, brings back the things you might not know about, but it's not the kind of next level creativity, which I think still humans are much better at.
And then ultimately what I think is the most important trait for a builder is judgment. Some people call it test making, but it's making high quality decisions in what is complex ambiguous situations. Everything else, I'm working really hard to automate. Really, really hard. And then when you think about the outcome, it's not just about having more shots at the goal, which I think people go like, "Oh, the iteration speed is going to be very high." Yes, but what you're really doing to an organization of at scale organizations is they're a lot more nimble, a lot more adaptive, a lot more resilient. They can navigate the future. They can actually match the pace of change to the pace of response.
And an analogy I have in mind is kind of Navy SEALs. You come to training, they're all kind of learning, they're cross-trained, across multiple areas. What they specialize in is the mission and they operate in small pods and they're very nimble and you can assemble them very quickly. And I think that's going to be the organization that will win in the future.

Lenny RachitskyOkay. So the simple idea, if you're just to boil it down to a sentence, the idea here is there's a builder who goes through the entire product development process essentially on their own. They have an idea, they research, they do data, they prototype design ship. That's kind of like the vision of where this goes?

Tomer CohenYes, but it doesn't have to be on their own. It's not like... I still believe in teams.

Lenny RachitskyGot it. So smaller teams.

Tomer CohenJust smaller teams. Smaller teams and much more focused on the problem, the mission, per say, versus... Actually, one of the things we've done as an example, we started to do the idea of pods. We're no longer large teams. We assemble a team, ideally a full stack builders coming together and it's less about can I have an engineer design PM working together and trying to combine this trio looking at folks who can flex across and then they tackle something for a quarter or so and then we reassemble those two different pods. That's one example of an manifestation we're doing right now and seeing actually some great success in both in terms of velocity, but also in terms of that focus and nimbleness of that team.

Lenny RachitskyAnd it feels like the goal here, what you're trying to adjust and that broke as teams bloated as speed and adaptability and flexibility, because going back to your original point that change is happening so much more quickly now that companies that have been building in this traditional way just can't compete.

Tomer CohenYeah. It's not that you have to break the model. I think the model is broken. It's just this pace of change is helping us realize it.

Lenny RachitskyOkay. So then going back to the things that these builders still do versus what you want to automate. So the list you shared is they're responsible for the vision, empathy, communication, creativity, and judgment.

Tomer CohenYes. Yeah. And I would put a lot of the focus on the latter. I think if you ask me at the end of the day, what's the kind of most important trait? I would say it's that judgment, test making ability.

Lenny RachitskyAnd then in terms of what you're automating, what are some of the areas you've seen a lot of success in actually automating and where do you think this goes?

Tomer CohenYeah. So I think just to kind of break it to pieces, and I think this is... If you were a startup right now, in many ways you can start this way. There's no legacy code, there's no legacy structure you run. And in fact, a lot of the startups I talked to that are built AI natively, they're just working at full stack builders. That's the way they start. If you're at a company at a scale of ours and many others in the market, you're like, this is almost like a new production function and mindset that you have to do. And there's really three components that we're working on. One is platform. The second one is the tools and the agents. And lastly is the culture.

The platform one, this is the kind of level of investment you have to do before, before this actually starts, you start to see all the benefits accrue. But the platform for us as an example is rearchitecting all of our core platforms so AI can reason over it. So we're building kind of this composable UI components with server side that we actually build. We're basically building for AI to be ready to bring it in. So you can't just go and bring a third party tool and have it work on the LinkedIn stack. In fact, that's one of our biggest learnings. It never works. Never works. You have to bring it in and customize a lot of it, working almost in alpha mode with those companies to make it work internally.

Lenny RachitskySo this is essentially re-architecting your code base to work more efficiently with AI. Is that one way to think about it?

Tomer CohenYes. And in many ways, working with those companies to adjust something in their stack to work with our stack as well.

Lenny RachitskyWhen you say those companies, meaning the development agents like Cursors and and such?

Tomer CohenYes. Or Figma on design. Or you can think about design systems is another example of that. But you have to have that back and forth because they're not... In many ways, we haven't seen anybody be able to work off the shelf immediately on our code-based design systems and unique context we have.

Lenny RachitskyJust to follow that thread briefly, so there's Figma. That's interesting. So basically the way Figma exports and keeps your design system, that has to change to work better with AI is what I'm hearing.

Tomer CohenThey first need to know how to work with our design systems, which is something, in many ways a lot of those companies are working on. Same with coding. It doesn't work that you just bring it in and it just reasons over your code base really well. We tried. We are building that layer that basically allows it to do so, whether it's Copilot or Cursor, Windsurf and so on.

Lenny RachitskyGot it. Okay. Oh yeah, Copilot. Microsoft. I get it. I get it. Okay. Okay. So that's the platform. So that's an investment that you guys have to make to make AI effective at building and doing all these things.

Tomer CohenAnd then you have tools. So tools is where you really build the agents. I mentioned I want to automate everything outside of those five trades that we talked about, and then we're building the tools for that. And then for that, actually very similarly, I can't just bring a tool from the outside and work. So I'll give you an example. One of our biggest things is building a trust agent. Trust is really important for us at LinkedIn. There's a lot of unique vectors which trust plays at LinkedIn doesn't place it anywhere else. So we need to bring all of that know how and context and information base into that agent. So we ended up building our own trust agent at LinkedIn.

Lenny RachitskyAnd so what is this trust agent doing? Telling you when you're maybe exposing information that you shouldn't be?

Tomer CohenSo when you build a spec, you build an idea, you walk through the trust agent and it'll basically tell you what are your vulnerabilities, what harm vectors potentially you're introducing or will be introduced as a result of that. And I had our head of trust build it. So the head of craft for every area is building their own agent. As an example, we have one of our features for job seekers is called Open to Work. If you're looking for a job, you can put an open to work.

Lenny RachitskyYeah, a little green loading thing on the circle.

Tomer CohenExactly. And actually it's a great signal. I've seen some great success from it. People are helping each other. The community really thrives around helping each other. But at the same time, it introduces a trust vector for bad actors because they're open to work. People who are looking for a job are potentially more vulnerable to scams than other folks. So being able to think about how do we prevent all of those ahead of time. So we walked that spec from a couple of years ago through the trust agent. Not only was it able to find all the stuff we initiated at the beginning, but all the holes that we did not catch until later. So that's a great example of something that actually worked really well.

That's one. The other one is a growth agent, as an example. Again, LinkedIn has a very unique... Actually, we have an incredible growth team, growth process. We've kind of funneled all of our unique loops, our funnels, our tests of the past, everything into this growth agent, and now you can basically rock your respect for it, your idea for it. And it would not just allow you to do it better. It would actually critique how good is your idea. This is something you cannot bring off the shelf. It's very unique to LinkedIn. So we had to invest dramatically in it. And one team which is using it right now, which is almost... I wasn't thinking about it at the beginning, but our UXR team, our UER team, the user research team is usually using that growth agent to understand out of all the things that are basically surfacing for members, which one has the biggest growth opportunity to have the biggest impact? That was not in the cards when we thought about that idea, but teams are basically funneling those ideas into this one.
An example is our research agent. So research agent basically is trained on the personas of our members. You can think about a small business owner, a job seeker and so on. And it's using not just world knowledge, it's using all the research we've done in the past, all the support tickets coming in. So it's pretty good at understanding that persona at LinkedIn. So one examples we had is a team came out with a spec. They weren't aware we had the research agent yet. I asked the research agent for a small business owner, wanted to think about the marketing spec we had, and it critiqued it extremely well. Actually, in many ways shifted the direction of the team to focus on other integrations tools we can focus on, but it's very hard to have that visibility all to all that corpus of knowledge inside of the company.
That's another example. We have an analyst agent trained on all how you basically can query the entire LinkedIn graph, which is enormous. And instead of relying on your SQL queries or data science teams, you can use the analyst agent. All of those I would say are, I would call them still MVP+. The goal for us in the next couple of months to basically roll them out externally. Externally, I mean, internally at LinkedIn.

Lenny RachitskyNot as new product lines.

Tomer CohenExactly.

Lenny RachitskyOkay. So many questions. One is just how are you building this? Is there a platform you're using? What does it take to build an agent at LinkedIn? Is it all internal tools or is there third party use?

Tomer CohenIt's a great call. So I think we've been experimenting with a lot of tools. And I would say for a lot of those kind of knowledge corpus agents, we're using everything from Copilot Enterprise to ChatGPT Enterprise. By far though, the most important part was basically our own customization of it. That's been where we saw the biggest gains. Even building the orchestrator across those because you want the agents to start following to each other, the trust agent should work with the growth agent and go do a back and forth versus doing what more sequentially. So we've done a lot of work internally to make it happen. This is why I think it does require that level of investment.

And then in some cases, let's talk about the design agent that we're working with. We're working with multiple companies to try and understand which product works best for us. And interestingly enough, and this is another learning, different teams gravitate to different products. So that's something we'll have to resolve and think about how we do this really well, because ultimately we were trying to simplify the process as much as possible, but that was a big learning for us and which tools we use and how we basically integrate them in.

Lenny RachitskyGot it. So you might have an amazing Figma agent, but some teams want to use a different design tool.

Tomer CohenYeah. So we've kind of experimented with Figma and Subframe and Magic Patterns and so on, and we saw people gravitating depending on the function, their level of visibility, their know how of the tool before, they're gravitating to different tools. And ultimately, I don't want to have eight design agents in the company, so we have to converge into at least a few. And I think it's similar across many areas because the appeal of those, a lot of those agents are trying to solve similar end goal, but they're doing it very differently. And what you'll see that ultimately, I don't think there's going to be a winner takes all because the starting point of the customer or the user will dictate a lot how simple they are for that use case.

Lenny RachitskySuper interesting. The other interesting takeaway here is you're designing very specific agents that are one job to be done. Is that a very intentional decision? Did you try an agent that just is super intelligent on all these things?

Tomer CohenUltimately, they will do an orchestrator. We're going to really orchestrator across, but we did want to be able to rate and grade those agents really well on how they're doing. And I think there is a level of expertise. Now, we're kind of building this in a way where we'll be able to mask a lot of those. You might not know that there's a trust agent. You might have, we call this internally the product jammer agent that basically does your product jam, which is a process we do internally. You might just use the product jam engine, and that product jam agent will work with all the other agents. But now we're starting with that building blocks until we build the orchestrating layer across.

Lenny RachitskyAnother interesting takeaway from what you've been sharing is that so much of the work has gone into the beginning of the product development process, just like helping you craft the right requirements, clarify trust, and then here's product jam and here's the research we've done. And I imagine it's because coding has already been accelerated with all these IEE tools. Talk about just why that's maybe where most of the investment's gone and where you've seen the most impact so far.

Tomer CohenWell, 100% our coding investment has gone, started a while back, and those are fall into place. We have our coding agent. In fact, we've kind of staged it into two parts of it. There is the idea to design part, and then let's call it the code to launch part. The code to launch part has gotten a lot of attention and we're making some big inroads there. Everything from the coding agent to what we call the maintenance agent when you have a failed build, it will do it for you. In fact, I think we're close to 50% of all those builds being done by the maintenance agent and a QA agent.

Lenny RachitskyWow. So this is when a break builds instead of engineers hopping on the issues that an agent fix.

Tomer CohenYou can still go and finish your coffee before you have to go and redo the build again.

Lenny RachitskyExtremely cool.

Tomer CohenBut we haven't had much investment until we kind of launched this program in the idea to design area. And that's a material part of work. It's also where the quality a lot of the work comes from, at least before you start to go into the coding phase. The idea is to empower everybody. So if you're an engineer, you can basically use all those tools at the front of the process and be able to be a full stack builder.

Lenny RachitskyHow long did it take to get this kind of in place for you to actually form your first team to build these, the initial agents and some of this backend, redo the code base sort of thing?

Tomer CohenI announced this internally end of last year, we really kind of started working, but it was more setting up the teams and the processes internally. We had our first MVPs of those agents I think like four to five months after it was really trained, I would say. But really the work itself has been kind of couple of months of dedicated work. A lot of it has been getting all the corpus of data together, cleaning it up. And that's actually a good learning as well. It's not great to just give it access to your drive and say, "Reason all over this knowledge base." It actually does a very poor job understanding importance of the past and putting weights on stuff. You actually want to think about specifically what the context when do you want to give it to and what's the knowledge base that you want to have it focused on. So even cleaning up, let's call them gold examples or golden examples to learn from, has been one of the biggest learnings. Just reasoning over your entire knowledge base did not work.

Lenny RachitskyYeah, that makes sense. There may be just like a researcher with a strong opinion about something that you disagree with and it wouldn't know. It's like, oh, of course, this is data, this is fact.

Tomer CohenExactly. And then it doesn't always understand ties to original specs to success. You have to actually build... This is a really interesting way. When you think about how you bring those tools in, you can't just bring them in. You have to know what you feed them with. And what you feed them with is not just access. I see a lot to just focus on the connectivity and integration and it reminds me of the... This is almost like, this is actually more than 10 years ago when I was co-rebuilding the team, co-rebuilding the feed at LinkedIn and we started from scratch and I had to literally sit down and filter through examples of what is a good professional post on LinkedIn and what is not. And this was like weeks of work getting up that golden sample of examples, but it wasn't... The most important part was feeding at the right data, not all the data.

So it requires work. This is where I would say for many companies who are thinking about this phase, and I do a lot of sessions today with CPOs and COs on this process. You have to put this initial work to get the gains after. When I think about it, I think there's a takeaway there in generally with AI, even if you're learning it for the first time and so on, whether it's Cursor or whether it's design, if it's Figma or other tools or Lovable, you should be ready to invest those hours before you start seeing yourself pick up in velocity and quality, which will come up, but you have to invest that time.
What's the current state of the pilot? How large is it? How many teams are doing it? What kind of stuff have you shipped? Just give us a sense of today's world.

Tomer CohenYeah. I wouldn't say we are yet at a very high sample rate where it's kind of a high percentage of the organization, but we have a substantial part of the organization already using it to provide a lot of the feedback. We're seeing a lot of great examples. So the way I think about the benefits is a function of experimentation volume multiplied by quality. How good are those experiments divided by the time it takes to actually pull them out, like idea to launch. So on saving times, we're seeing, whether it's PMs, designers, engineers, saving hours of work a week right now, whether it's the analyst agent we talked about or the prototyping really quickly or the product jamming experience has been a big part of that. On the quality side, we're seeing insights discussions just be much, much better. And by the way, quality and time, sometimes they help each other because it's high quality, you don't have to spend as much time on something.

So we are seeing that applied in. And the volume, I wouldn't say we had a rate where I'm seeing a high percentage organization doing it yet, but this will come once we... We haven't GA'd this internally. That will come in the next couple of months once we have all the stuff in place. But we're seeing designers and PMs picking up bugs directly from Jira tickets, pushing them in, something we haven't seen before, and there's just an appetite for everybody to just join. So in fact, the biggest thing right now is everybody wants access. Everybody wants access to the tools to be able to do it together, and we just want to make sure it's good enough to make sure the whole organization can do it really well.

Lenny RachitskySo how is it that you're piling it? Is it some number of people have access to these agents and they just work the way they've worked with access to these tools? Or is there a team dedicated, this is the way you work now and this is it, and we'll see what happens.

Tomer CohenSo that's a great call. So basically we have a team building. It's the core team building the FSB track across all of R&D, FSB, full stack builder. And then there are pockets and pods of teams using it. So basically we are looking at specific areas that we're basically giving it to. The condition there is they give feedback. As a response for that, they make the tool better, so it's not just access. We want people who will use it. So one of your early adopters would be the ones who help up the product really well. So we're doing this in a pod model right now.

Lenny RachitskySo it's like a pod within a larger team, like a designer, PM, engineer kind of group within... Is there an example? You have a part of LinkedIn that's trying this out?

Tomer CohenYeah. So if I think about some of our teams, whether it's... Actually, we just launched Semantic People Search and the Semantic Job Search as well. That team was using part of those tools to actually help build it. So that team actually, this was PMs building their own dashboards with those tools without waiting for design resources to come in. Then we have a design team who is now... This started really from the manager rolling this out. And in many ways, what I tell this team is, "Don't wait for the official GA. Start doing it. Start leaning in." We're seeing designers of that team starting to push PRs, which never happened before. And now other teams, they want to do this as well. So it's starting with this kind of grassroots experience. I would say the places have been very formal. I would say the beginning has been the top.

The product executive teams, basically we move from functional leaders, design, PM, BD, and so on to product areas leaders, and they basically rock across the stack and they also go for a 360 with all of those functions to see if they're really able to do a full stack building experience. Then we're also launching at the junior side a new program called the Associate Product Builder Program, where basically we used to have our APM program, which this is about it's ending this year. And then starting January, we're going to start having our APB program and they're going to come into LinkedIn. We're going to teach them how to code, design and PM at LinkedIn. They're going to go through a pretty rigorous training process, and then they're going to join those pods, and gradually we're going to grow that program to be a material part of LinkedIn as well.

Lenny RachitskyWow. So this might be the future of the APM program is this full stack builder APM-ish program.

Tomer CohenIn many ways, we've built some pretty amazing... I'm really excited for that group. I wish I could join it. But we build amazing training for them. And in many ways, we're going to use that training to think about how we roll it across the organization. We're kind of using the lens of you have great technical skills, but you're not an engineer at a company yet, or you have great design taste, but you haven't designed at scale in company yet, and we're going to teach you how to do it at LinkedIn, but the training we're going to use a lot to extend across the company as well.

Lenny RachitskyOkay. So you have these programs, these pilots and these pods, and you said what you're looking at to see if this is something you roll out is experiment velocity times quality times time.

Tomer CohenDivided by time.

Lenny RachitskyDivided by time. Okay.

Tomer CohenYeah.

Lenny RachitskyGot it. And I guess I know it's early, but just you said you're seeing that it's saving teams a few hours a week at this point, something like that?

Tomer CohenYeah. And I think the feedback has been the most important part. Right? The way to think about this is just like you build a product. So we're building this product internally and you want to experiment with some kind of early adopters who will give you feedback, and the feedback has been amazing. In fact, our top talent are the ones who are using this the most at LinkedIn. And the feedback from them has been incredible in terms because they're also willing to spend the time and give the feedback as well. And the response from them has been incredible in terms of like the quality of their output, the time they're spending on this to get the value back, their desire to be part of this and actually scale this and make this even better. So that's where a lot of the excitement has been from how they're using it and the quality we've seen there. I would say in six months or so, we'll be able to see a lot more of the organization use it and you'll start seeing those top line numbers will build as well.

Lenny RachitskyThat is a really interesting insight that the top performers are finding the most success, because there's always been this question, is AI going to just make people that are not amazing, more amazing, or is it going to make amazing people even more amazing? And it sounds like it's likely the latter.

Tomer CohenYes. And in many ways, it's surprising, it's not surprising. I've seen this also when we were... It's surprising because you want everybody else to be part of this and lean in. I think top talent has this tendency of continuously trying to get better at their craft and this innate need to be at the cutting edge of how you build, and I think we're seeing this here as well. This is why I had this phrase I say with the team that if we build all those tools, will they use it? And I know right now the answer is no. It's not enough to give them the tools to use it. You have to build the incentives programs, the motivation, the examples to how you do it. They need to see other people being successful as well.

And I've seen this also when we're shifting LinkedIn from a desktop company into a mobile company. It was a very similar process. It's very hard. Change management here is going to be a critical part. I think I see a lot of companies roll out their agents and just expecting companies to adopt. It doesn't work this way. Some will adopt. That tends to be your cutting edge 5% of talent that just wants new tools and they have a bias for change. But the vast majority needs to work for change management in how they do it, and that requires being a lot more thoughtful about the cultural aspect of it, which is by far from me the biggest and most important thing to do.

Lenny RachitskyYeah. I want to spend time there. And it makes a lot of sense why people don't spend time here because they have so much to do. They got to ship things. Their days are already busy. You have to now carve out time to learn this new tool that'll not pay off for a while. So I get why people are like, "Okay, okay, I'll get there. I'll use it someday," but they don't. This idea of culture, when I saw you share this initially, this is the third piece of making this successful. So there's the platform of getting the code base ready for people for AI to work with. Then there's the tool, like the agents you've talked about, and then there's the culture. Is there more there that you can share of just what has actually worked in helping get people on board? One thing I heard is creating a little bit of FOMO of like, okay, only a few people can use this and you have to sign up to get access. What's worked in getting people to get on board?

Tomer CohenYeah. I think this is where I emphasize to people that getting everything done, the platforms, the tools is not going to be sufficient. It's a prerequisite for this to work, but not sufficient for this to work because it really requires you to invest a lot in the cultural aspects of how do you get people to lean into this one. And this one might feel slow at first, but I've seen this before with our transformation of thinking from desktop to mobile. And once it picks up, it actually maintains very high velocity. One, people are really incentivized by how you define expectations for them. So to think about what is the expectation of somebody in the role, whatever-

Lenny RachitskySo like changing performance review sort of things.

Tomer CohenVery much so. So everything from how you hire to calibration and evaluation. And one thing I want to see there early is this kind of AI agency and fluency. Like I mentioned, the tools are there. The question is, would you use them? Because the tools will be good enough, but not great at the beginning. That's the classic thing of every good MVP tool. They're good enough, but they're not great. And then you kind of want to build that agency to make the tool better. We're in this kind of notion of we're going to make this better for LinkedIn together. Two is piloting success inside of your organization. That's the pod model where you're showing that not only this could work, it's actually having success. So we have even our partnerships team, our BD team, being able to go instead of relying on waiting for an engineer to help build the developer portal and build the connectors there.

Literally one of our head of partnerships just went and did it himself. Didn't even delegate to his team. And their goal is to say like, "Hey, I can do it. You can do it as well." Those examples are really, really powerful. I talked about the associate product builder program where we are going to be very focused on training. I think that will send a really strong message across the organization. People will see this talent and what they can do, and I think that will create that movement. But celebrating wins in all hands, highlighting people and showing those examples. One example we've seen recently, people really looked at it in a surprise lens, but then it kind of, I think, really opened up a lens for them. We had somebody in our user research team. We had an opening for a PM on the growth team, and that role was open for a while, and she said that, "I think I can do it."
And she used all these tools. This is a user researcher becoming a growth PM, not usually the career path you see, but she was excited about the area. She used all those tools, and she's now a growth PM on the team. And really, you can start thinking about her more as a full stack builder ultimately. But seeing those openings and then highlighting those two people, actually people who are doing this have been a great example of it. And then just making sure that those tools are accessible. People can provide feedback, you share a lot, has been an incredible part of this. It's not enough to be top-down directive that this is how we want to work. People want to feel like there are success stories. They feel like it's worth their time. It feels it's a movement they want to be part of, and then ultimately they can see successes in how they do it.

Lenny RachitskyI love this kind of comparison to the shift to mobile. We all went through that and there's all these stories of companies requiring you to show mobile mocks. That's the only way we're going to operate. Now everything you have to ship has to be on mobile, and it's interesting how similar this is to them, to that experience. And so a few things you just shared here just to kind of summarize some of the things that have worked for you. Showing wins, celebrating wins, showing people what other folks are doing with AI tools, creating a program that people enroll into and make it a little bit exclusive. This performance review piece is really interesting because that really will change people's behaviors. Here's how we get promoted. Have you actually already made that change to the PM? I guess it's every track, I imagine, not just product management. Have you already made that change or is it kind of like a work in progress?

Tomer CohenSo there was two aspects to it. Once I moved my team, my directs, we did 360 for them. So their 360 was, if you came from PM, you had the designers on your team rate you. And so that had its own, and then we shared those with them, and that had its own kind of motivation. But then we broadly took it across. So when we hire right now, we look for those. And then this upcoming cycle, we do a bi-annual. That's going to be part of the performance evaluation piece and we announce it to everybody. And for what, it's where people are excited to show. And they're excited to know how they're going to be... It's always about, like, "I want to know how I'm being rated or evaluated." So just being able to show those examples has been a big part of it.

The other thing I would say, it takes time for this program and its formality to roll out across the entire organization, and I was intentionally not trying to be quick at rolling this out to everybody because I think that just dilutes the value of it really quickly because it's not about... I could care less about your title. I care about how you work. So calling you a full stack builder is not what I'm looking for. Changing your mindset to a full stack mindset is what I'm looking for. You're thinking you can do the whole thing. You're looking at those tools and looking at how to do it.
So one of the things I've said is if you're looking for a formal reorg or declaration to start building differently, you're waiting too long. Look, my biggest thing is here's a permission for me to just not wait and just go. So whether or not you have the right tools or not, go build the tool, use a tool from the outside, bring it in, show those examples. In many ways, prove that you are a full stack builder in mindset before anything else come to mind. And that just naturally will happen, and that's also where we've seen some of our best talent just goes and leans a lot into.

Lenny RachitskyI love that. I was going to actually mention that quote. Someone you shared, you work with told me exactly that quote you just shared, so I'm glad you brought it up of just if you're waiting for a reorg, you're not thinking about it the right way. How do you encourage people to actually play with these tools on their own? Are you just like, "Go take a few days to play with AI?" Is it just try it? Or is there anything formal you've seen of just getting people to more try this on their own without joining this program?

Tomer CohenA lot of the tools we've made, we've been sharing them regularly. A few of my all hands have been all about how to use those tools. But then at the same time, we're kind of inviting, have you found a new tool that works really well for you? Share it, show it. Again, it could be Slack, could be Messages, Teams and so on, how you do it. But the idea is really to start getting that investment in how things work. Actually, I think in general, you can feel overwhelmed by tools right now, by recipes and how to do things like what's your prompt and what's my prompt. But really it's finding something that kind of works really well, that can gravitate around and really invest in that's been those areas. But I think we've had this invitation to go and explore and go and bring in stuff that you think are great. And in many ways, bring others along on the journey. It's one good way to make the influence much bigger than a few folks who are doing really well with this.

Lenny RachitskyAre there any surprises on the negative side that have come out of this, of PRD is just feeling like AI driven, people slowing down unexpectedly? Is there anything that surprised you of just like, "Okay, this is actually not great"?

Tomer CohenYeah, we mentioned a few of them. I was hoping for some tools to work off the shelf really well. It was never the case because we had to invest quite a lot.

Lenny RachitskyNever the case.

Tomer CohenNever the case. We had to invest quite a lot. And again, part of it is we just have a lot of legacy information and code based and knowledge and designs and so on. So a lot of the companies we work with are seeing this as a great growth opportunity for them as well to invest, but I do think it's a big area of investment as well. We talked about not just giving access to all of your context which we started with, and we were like, "Oh, here's access to all the drive, all information," failed miserably and hallucinates like crazy." People gravitating towards different tools, like our goal was to converge on tools, but that was pretty hard.

And then I think in terms of quality, we've just seen better quality, but I think it's because, again, where we are in the stage is still the early adopters and they're doing a few iterations in terms of how to do it. But I would say the tooling adoption is hard. And then I think for some people, this is important for me to kind of state, some people do not want to be full-stack builders, and that's completely okay. Some people see themselves in specialization, and I think specialization has a place and a role. So I didn't want the message to be across the organization I expect everybody to be a full-stack builder. I do not. I think there are system builders that empower full-stack builders, and then you have people who are specialized. But I don't think we need as many specialized people as we did in the past.

Lenny RachitskyI didn't actually realize this until just now. So is this their title now instead of product manager engineer, they're full stack builder?

Tomer CohenWe have a full stack builder title formally inside the organization, and we are gradually putting people in that bucket.

Lenny RachitskySo there's a whole career ladder that's forming. There's a whole... Okay. That's a bigger deal than I even thought. So where are you finding these folks mostly coming from, like product, engineering, design? I imagine it's a mix, but just is there a most common trend?

Tomer CohenIt's a mix. People listening, I would just think about just go over your org and imagine who can do it, who can right now flex across those functions, whether it is engineering, design, product, even BD, and what you'll find is there's already quite a few that can flex across.

Lenny RachitskyInteresting. Are there any functions you think are especially successful at this? Not to play any favorites, but I don't know. Are you finding like, okay? Or you could also not highlight any specific.

Tomer CohenNo, I think it's a mental model of how you do it. I think if I were to play what's the hardest craft to potentially learn, I think design has a lot more work to get the design agents to be really, really good. So I think designers have a little bit of a leg up in terms of others learning their craft than the vice versa. But I honestly think it's a mindset. I've seen designers code, I've seen PMs kind of design and do well. And this is why I think when you kind of step back and you think about people in your organization and who can flex, I think you'll see them show up in many areas. And what I think you'll find there is they have the agency, they're leaning into new things, they have the fluency, like they're already building new experiences and they have that growth mindset that they just want to get better, so it doesn't matter what they learn at school or what label somebody put in them when they join the company.

Lenny RachitskyWhat I love about a lot of this is it's the easiest time to transition between different product roles than it's ever been. Design's moving to PM, and sure, or just moving to this new role, it makes it so much easier to, like you said, that researcher became a growth PM.

Tomer CohenAnd this is probably my biggest advice slash motivation I give to the team because what I tell them is ultimately... By the way, this is for me as well. I think about it the same way. The incentives for you are so aligned with your organization of what we're asking for, right? Because we need you to change. We want to be a more agile, adaptive, resilient organization that can deal with the pace of change, but you want as well for your own career. You want to be at the cutting edge of how you build. So the incentives are really aligned between what you need for your own career and what the organization needs you to do. So there's that permission to go and do it for me is ideally kind of a tailwind in what they want to do more than anything else.

Lenny RachitskyMaybe a last question for people that are inspired and like, "Okay, this is what we need to be doing," any just tips for someone starting down this road to be successful at trying something like this at their company?

Tomer CohenI would say I would start with the notion of how do you want to bring this just structure. I would think about the platform you need to build, the tools you want to bring, and then I would spend a lot of time on the culture. Platform and tools I think would be, again, a prerequisite, but not sufficient, and the cultural aspect is really important. I would think a lot about how you bring people along. So for one of the learnings we had that probably able to do it differently right now, if I were to redo this program was, for a while I was working very closely with my core team on it, the core kind of full stack building team that were in charge of building all this material, but the organization was always asking questions. "What's going on? Who is doing it? What are the tools?" And in retrospect, we could have done a lot more in the flow to just show them and get them to already use early tools or be aware of it versus doing a small team on the side.

So it's okay to start with a small team. I think it's really important. But at the same time, just making sure there's visibility across the whole thing is really powerful. Being patient and being willing to invest. I always give this example of, we always give this example of like, "Oh, look at this startup. They built this in a week." Yes, you can build lifestyle in a week right now if you start from scratch. It's actually not hard. But when you are trying to transform a large organization, you want to have this impatient about the goal and you have to have a high ambition, but being very thoughtful and patient about how you bring it to life and the key things you have to invest in. If you don't invest in your platform, I just don't see how this could be a successful outcome. If you don't invest in customizing the tools for you, then you're just going to get vanilla generic agents from the outside.
So being aware of the investment and making sure you actually allocate resource to it, this is kind of the classic, be willing to invest upfront so you can reap the benefit after, versus saying, "Hey, why am I not seeing us moving into 2X the productivity in a week?" That's not going to be this way. You can see it with some people, but starting to collect those examples and starting to really think about the transformation is really key.

Lenny RachitskyThis is so incredibly cool. I know that a lot of CPOs and heads of product and all kinds of leaders are reaching out to you trying to figure out what you've learned how to do this. So I love that we went deep on all these things. Just final question, is there anything else that we haven't shared that you think might be helpful for listeners to hear or maybe just to double down on before we get to our very exciting lightning round?

Tomer CohenWhether you're in an organization, you're waiting for your leader to roll this out or you're a leader trying to roll this out, I would not wait. The first thing I've done, which I thought in retrospect was very hopeful is I did announce this upfront we are going to this mode. We're starting in pockets, we're starting in pods, we're building the tools, but this is the mountain we're going to go after, and in many ways, we're going to make it great. I also announced that this is not just an end state, it's a kind of continuous progress. There's no state we're going to get to as much as continuously just trying to be better. And in many ways, to compete, you just want to be better than others in how you build because the version of building will completely just transform itself every few years or so.

So do not wait. Really focus on the progress you're making, over communicate with your team, not just the vision, but also the progress you're making, almost like holding yourself responsible. If you're a leader, give yourself KPIs you share with your own teams or OKRs. And if you're inside of the organization, and I would say whether or not or not your CPO or your CEO is announcing this type of program, go do it or join an organization that does it so you can be at the cutting edge of how you build in the future.

Lenny RachitskyTomer, with that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready?

Tomer CohenI'm ready.

Lenny RachitskyFirst question, what are two or three books you find yourself recommending most to other people?

Tomer CohenI love to give trios of books that I really like. So my current trio is, they're very diverse in topics, so apologies if it's not falling all into tech. But the first one is called Why Nations Fail. It's a book I read a decade ago even more and the authors of it just won the Nobel Prize last year. And it basically talks about why does some nations succeed and some fail? And it's not the usual explanations we go for, which is, oh, it's culture, it's natural resources, it's the kind of religion. A lot of those tends to be the kind of immediate excuses people have. It kind of falls into two camps. Are there extractive or inclusive institutions? Can people participate broadly and opportunities shared or there are institutions that basically are supposed to be attracting from many and give to some.

So it's just an incredible way to just think about how you build a nation. And for us at LinkedIn, we think a lot about the idea of opportunities, so how you build a product as well. And it's just a good way to move away from easy explanations into what really makes a country really successful as well. Second book, it's called Outlive. It's really about the idea, it's kind of like the author, Peter Attia talks about the idea of medicine 3.0, which is really the notion of building personalized medicine, which I think in the world of AI will become incredible in the future. But it's all those, let's call those categories that you should think about for your life so you can just optimize your health as much as possible and goes for everything through fitness to diet to the biggest health factors you should think about. But it's a great long book. Then lastly-

Lenny RachitskyThe one in my bookshelf behind me.

Tomer CohenThere you go.

Lenny RachitskyIt's up top. You can't actually see it, I think.

Tomer CohenAnd then lastly, it's a book that also came out many years ago, but it's called The Beginning of Infinity, which I really like, by Deutsche. It wasn't an easy read for me, but I love the idea. In fact, especially in products, I love the idea of cause and effect, like really finding great explanations for why things happen and then building on top of that your next iterations. And this book really pushes on the idea of explanations that only once we have a clear understanding of what things happens, then we can have breakthroughs on top of that. But until we get to a point of clear scientific breakthroughs, we are not going to make significant progress. But when you do that, it's really almost like infinite progress you can make on top of that.

Lenny RachitskyNaval's always talking about that last book. I think I bought it and it was just hard reading this.

Tomer CohenIt's not an easy read, at least for me. It wasn't an easy read, but it's a very powerful read.

Lenny RachitskyAwesome. Is there a favorite recent movie or TV show you really enjoyed?

Tomer CohenCan I do a podcast?

Lenny RachitskyAbsolutely.

Tomer CohenSo there's a podcast in, it's in Hebrew, it's called One Song, and it takes a song that generally is ideally popular and then goes really deep on the origin and the history of the song, and I love it. I love music and just dissects songs so well. It does a great job also in bringing to life the story behind it. So for me, it just goes back to you thought the song was about something, but then it goes really deep into the actors behind the song, and sometimes it's the words chosen or it's how the lyrics match the music itself, and I just really enjoy that one.

Lenny RachitskyThere's a podcast called Song Exploder, I believe, that is a similar concept that's not in Hebrew, in English, that I'll point people to if you love that one.

Tomer CohenThat's awesome.

Lenny RachitskyIs there a product you've recently discovered that you really love? Could be an app, could be some clothing, could be a kitchen gadget, type gadget.

Tomer CohenCan it can be a product I want to have, which I think is actually really easy to do?

Lenny RachitskyI love that. This is a product thinking 101 and just the vision of what you want to see.

Tomer CohenSo in my car right now, there's Alexa built-in, which is great because the kids can ask for songs all day long and it's a whole show inside of the car. But one of my favorite things to do when this has been doing it for well over two years is I go in and I go into voice mode.

Lenny RachitskyChatGPT.

Tomer CohenYeah, ChatGPT, and then just have a conversation, and that's just friction. I would love to have on my steering wheel a button that invokes my AI friend that can sit next to me in the passenger seat, and I just think that would be such a... I actually think it would rides for people. Just that movement, that's just like elimination of friction will transform the experience for me.

Lenny RachitskyOn that note, I recently discovered Teslas actually do this now. If you hold the right wheel, Grok appears and you could talk to Grok. So it's here. The AI has arrived. Yeah. I just did it by accident and then it's, "Okay, cool."

Tomer CohenGreat. So for me, if anybody from Rivian is listening, please bring this in the car.

Lenny RachitskyRivian's falling behind. Yeah. And you have to use Grok. It'd be cool if you could switch to different AIs because it has a personality. Just give me information. I don't need you to laugh and give me jokes.

Tomer CohenDid you need to spend some time with it before or did it have any memory from... Did you bring any memory into it?

Lenny RachitskyThere's a logged out version and then you could just log in and it connects to your account. Yeah, it's extremely cool. No one's talking about it. It's crazy because I don't know if they launched it fully, but it just appeared.

Tomer CohenDo you talk in the car a lot to it?

Lenny RachitskyI don't use it that much, to be honest, but I should. My wife just doesn't love Grok. I think the brand of Grok is a specific brand. And so she's like, "Don't talk to Grok in here with me."

Tomer CohenI love voice mode, so I use it all the time.

Lenny RachitskyYeah, I love voice mode too. It just interrupts too often. That's the issue there, right? It's just it stops.

Tomer CohenBy the way, you can set it up. You can basically say like, "Hey, just let me finish."

Lenny RachitskyI now know that. I'm learning so much. Okay. Two more questions. Do you have a life motto that you often find useful in work or in life?

Tomer CohenI think last time I talked about it, I most associated here with, I might be wrong, but I'm not confused, although I don't say it as much anymore. But I think the one I love, growth mindset is a second religions for us at home. And one thing I love about, there's a phrase there that is becoming is better than being, which I think ties into the FSB mode a little bit, which is you're always in progress mode, iteration mode. It's not about reaching a state. It's about the journey, the process. That's what you should fall in love with. It's about continuously growing and evolving without the negativity of it or there's no sense of FOMO there. It's just this continuous thing. If I look back a year from now and I look back, how much did I grow? How much do I know? What skills to do that again? Where are I becoming better? Do I feel like Tomer version 2026 versus 2025? What's the delta there? And I kind of love that as a way of thinking.

Lenny RachitskyA great segue to our final question. By the time this episode comes out, it won't be a secret that you're leaving LinkedIn after 14 years. Legendary run. You joined way before the acquisition, you helped them integrate. Just like the way LinkedIn was perceived 14 years ago is so radically different from the way it is today. It's actually really fun and interesting to be there versus how people for a long time felt about LinkedIn. So I guess the question just how you feeling and what's next? I imagine you're going to get a lot of calls from a lot of people, but what are you planning?

Tomer CohenYeah, so I feel proud. It's been an incredible ride at LinkedIn. The way I've got to know about LinkedIn deeply the very first time was when I moved to the Valley and I went to a lecture at Stanford about social networks in 2008 and Reid was there and he talked about the power of being a professional communities online, and I was very nerdy about it and thought it was incredible vision, had no plans to join and actually started my own company after. But as luck would have it, found myself joining a few years after and just thought the mission was incredible. So in many ways it aligned with my purpose and just was an incredible ride to be here.

And I also feel very grateful. I shared this with the company recently. I was starting to take learnings from my experiences here. A lot of it was from tough situations. We had a lot of tough situations at LinkedIn and hard calls and late nights, but you learn so much from those and I'm just incredibly grateful. And I'm excited. I'm excited. I have a bias for change. I have a bias for kind of positioning myself in a place where I can learn the most and learn a lot. And it's an incredible time to build, so I'm just excited to be thinking of new problem sets and new areas where I can go deep on and invest the next decade in.

Lenny RachitskyI think it's going to take a long time for you to not feel like you're working on LinkedIn and to forget about all the things that you have been worrying about for so many years.

Tomer CohenAfter you build something for such a long time, and I think you and I talked about it at one point, that I think one of the best traits for a builder is to become very passionate with what they're building. Really care. Not about the job. It's really care about the product. When you feel the pain when somebody complains and you kind of have this continuous discontent, and it's like for me, it's the notion of raising a baby. So yeah, it's hard. It will be hard. I will always think of LinkedIn as one of the babies I helped grow.

Lenny RachitskyWell, I'm excited to have you back someday when you figure out what you want to do next and or start whatever you're doing. I love that this was an excuse to get to know you. Tomer, thank you so much for being here.

Tomer CohenIt was great to be here. Thanks, Lenny.

Lenny RachitskyBye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lennyspodcast.com. See you in the next episode.

章节 02 / 08

第02节

中文 译稿已完成

Tomer Cohen我们看一个人做这份工作所需的技能,到 2030 年会变掉 70%。所以不管你想不想换工作,你的工作本身都在变。要想保持竞争力,你其实得回到一些最基本的原则,回到白板前,重新想一想“构建”到底意味着什么。

Lenny Rachitsky你们在 LinkedIn 试着用一种完全不同的方式做产品,基本上是把 AI 能释放出来的能力都吃进去了。

Tomer Cohen我们把它叫做 full stack builder 模型。目标很简单,就是让优秀的 builder 能把自己的想法带到市场上,不受岗位、技术栈和所在团队的限制。本质上,这是人和机器之间更流动的协作。

Lenny Rachitsky这听起来像是很多公司未来的运作方式,也可能是产品最终会被构建出来的方式。

Tomer Cohen这里变革管理会是关键,但光给工具还不够。你还得配套激励机制、行动动机,以及怎么用的示范样板。我看到很多公司把 agent 推出来,就指望公司自然会采纳。这不是这么回事。

Lenny Rachitsky一直有个问题,AI 到底只是让普通人变得更强,还是会让顶尖的人变得更强?

Tomer Cohen顶尖人才往往会不停地打磨自己的手艺。我特别强调 builder 要有的核心特质是……

Lenny Rachitsky今天的嘉宾是 Tomer Cohen,LinkedIn 的长期首席产品官。他正在试一种我认为未来很多公司都会采用的新做法。这个项目叫 Full Stack Builder Program,核心思路是让任何人,不管负责什么,都能把产品从想法一路做到账。LinkedIn 甚至把 APM 项目砍掉,换成了 Associate Full Stack Builder Program;还新设了一个叫 Full Stack Builder 的职业路径,任何职能的人都可以走这条路。你等会儿会听到,他们还搭了一堆内部工具、agents 和流程,基本上是在组一支人和 AI 混编的产品团队,让它跑得更快、适应变化更快,而且用更少的人做更多的事。如果你想重新思考团队怎么运作,想看看 AI 到底给团队和公司释放了什么能力,这期会很适合你。

我的播客嘉宾和我都很爱聊 craft、taste、agency 和 product-market fit。那我们不太爱聊什么?SOC 2。Vanta 就是干这个的。Vanta 帮各种规模的公司更快完成合规,并且长期保持合规,背后有领先的 AI、自动化和持续监控。不管你是初创公司在搞第一份 SOC 2 或 ISO 27001,还是企业在管理供应商风险,Vanta 的信任管理平台都能让流程更快、更简单,也更容易规模化。它还能把安全问卷的完成速度提高到原来的 5 倍,让你更快拿下更大的单子。根据最近一项 IDC 研究,Vanta 用户每年能省下 50 多万美元,生产力还提升到原来的 3 倍。建立信任不是可选项,Vanta 能把它变成自动化。到 vanta.com/lenny 可享受 1000 美元优惠。
本期节目由 Figma 赞助,Figma Make 的出品方就是它。以前我在 Airbnb 做 PM 的时候,还记得 Figma 刚出来那会儿,它把我们团队的协作方式改得特别顺。突然之间,我能把整个团队都拉进设计流程里,也能很快对设计概念给反馈,整个产品开发过程一下子就有意思多了。
但 Figma 以前总觉得不是给我这种 builder 准备的。它很适合反馈设计,但作为 builder,我更想亲手做东西。所以 Figma 做了 Figma Make。你只要输入几个提示,就能把任何想法或设计变成可运行的原型或应用,任何人都能继续迭代并和客户一起验证。Figma Make 是另一种风格的氛围编程工具,而且因为它全都在 Figma 里,你可以直接用团队现有的设计积木,产出更好看、更像真的、也更贴合团队构建方式的成果。别再花太多时间跟别人解释你的产品愿景了,直接把它做出来给他们看。用 Figma Make 快速做出有代码支撑的原型和应用,去 figma.com/lenny 看看。
Tomer,非常感谢你来,欢迎回到播客。

Tomer Cohen谢谢,很高兴再次回来。

Lenny Rachitsky很高兴你回来。我特别期待这次聊天,因为你们在 LinkedIn 试着用一种完全不同的方式做产品,基本上是把 AI 能释放出来的能力都吃进去了,也顺着这些新能力往前走。对我来说,这听起来像是很多公司未来的运作方式,也可能是产品最终会被构建出来的方式。现在有很多产品负责人都在谈 AI、谈它能做什么,但感觉你们是真的在用一种非常非常激进的方式把它落地。所以我很想向你学习,也想让听众听懂你们看到了什么、学到了什么。先从一个最基本的问题开始:你为什么觉得这件事必须做?为什么要重新思考那些产品长期以来一直沿用的做法?换句话说,为什么大家一定要注意我们接下来要聊的这些东西?

Tomer Cohen一切都要从最基本的地方说起。对我来说,技术一直都关乎赋能。它的重点不是它替我们做了什么,而是它让我们能做什么。现在,在我看来,我们有一个很棒的机会,可以把它变成一种真正的机会均等,但这不只是机会,也是当下的必要选择。我想把它放到一个更大的背景里来看:我们正在进入一个“变化的时间常数”远远大于“响应的时间常数”的阶段。说白了,就是变化发生得比我们来得及回应更快。LinkedIn 又恰好能看到工作世界的一个独特切面,所以我们有一些在我看来很震撼的数据。看一个人做当前工作所需要的技能,到 2030 年,也就是四年后,会变掉 70%。

所以不管你想不想换工作,你的工作都在变。唯一的问题是,你能不能跟上。再看组织层面,眼下增长最快、市场最缺的那些岗位,跟去年增长最快的岗位相比,增速都在 70% 往上。也就是说,组织要想活得好,需要一套新的演化逻辑。把这个视角放到产品构建上,你就会发现,要保持竞争力,就必须回到一些第一性原理,回到白板前,重新想一想“构建”到底意味着什么。我很喜欢的一点是,当你想 builder 这个角色时,你会发现它其实就是公司的核心。它的目标很简单:builder 拿到一个 idea,把它变成现实,就是这么个过程。我们都在做那些所谓的 best practices:先把问题研究透,再写规格、做设计、写代码、上线、迭代,基本就是这样。
但在很多规模化公司里,包括 LinkedIn 在内,这个过程很快就变复杂了。怎么变复杂的?每一步都被我们拆成了很多子步骤。比如“研究问题”,在我们这儿就意味着要看 10 到 15 个信息来源,当然还包括跟客户聊、做数据分析、看多种渠道里的反馈工单、看社交媒体、看和客户的互动。只有当我们真的把研究做扎实时,才会去看这些十来个信息源。
再比如产品评审,有设计评审、隐私评审、安全评审,我还能继续往下列。每一个子步骤本身都不是没道理,它们存在都有正当理由。但你把整件事拼在一起就会发现:“天哪,为什么做一个小功能要扯上多个团队、多套代码库、多个 sprint,才能推上线。”而且还没算迭代,那才是真正决定成败的地方。你从来不是在上线那一刻看到成功的。问题其实不是工作本身复杂,而是我们把流程做得太复杂了。我继续往下拆的时候发现,事情不止于此,因为这些子步骤总得有人来做,所以你实际上是从流程复杂,走到了组织复杂。
然后就会进入微专门化。所有这些子集都被非常具体的人承担了。原本一个 builder,现在变成了多个职能。我们当然有工程、产品和设计,而且你已经可以开始质疑这些边界了,至少我在内部是这么做的。再往下,每个职能里还有更多子专业。设计里就有交互设计、动效设计、内容设计、研究,太多了。它们每一个都合理,但每一个都对应着人,这整套系统最后就变成了……本质上就是膨胀,就是复杂化。然后你甚至没意识到,自己已经掉进了一个极其复杂的体系里。我们其实有一张图,专门把流程复杂和组织复杂画在一起。
大多数人看到的时候都会被震住,因为他们平时只是在做一个很具体的点;可一旦你把镜头拉远,你就会看到整个体验复杂到让人喘不过气。现在我们正好有一个真实的机会,把整套栈往回收,回到工艺本身,重新思考产品开发生命周期,而这就是 full stack builder 模型真正活起来的地方。

Lenny Rachitsky哇,这里面东西很多。你讲的时候我们会把图也放出来,方便大家跟着看你在说什么。这一整套逻辑从理性上看其实很顺:如果你有 15 个信息源,为什么不用?为什么要错过那些东西?你描述的其实是,能力越强、分工越细,逻辑上都说得通。可一旦你退后一步去看,就会发现,天哪,做一个功能居然要六个月。我想问一个你刚才提到的数据。我觉得这个数据特别有力量,而且你们手上确实有很独特的数据去支撑它。你说,大概 70% 的未来所需技能会变化。

Tomer Cohen是为了完成他们当前的工作。

Lenny Rachitsky是为了完成他们当前的工作。那这个数据是怎么看出来的?是只看历史数据,还是你们怎么得到这个结论的?

English No English text found
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章节 03 / 08

第03节

中文 译稿已完成

Tomer CohenYeah,老实说,变化一直都在发生,对吧?所以它从来不是“把今天已有的技能原封不动保留下来”这么简单,只是我们以前从没见过像现在这样剧烈地重塑一个人岗位的一部分。现在不管你是营销、销售、招聘还是工程师,都会受到影响。工程尤其如此,因为 agent 相关的投入现在大多投向了工程岗位。这些工作会发生剧烈变化。我还记得自己当工程师时的样子,就算只是我自己的职业生涯,十年后也已经发生了实质变化。再看眼下这波变化,光想四年后“真正把工程做得特别好”需要什么,答案就会完全不同;做软件、做某种产物也是一样。但这几乎适用于所有职能。影响并不平均。像护士这样的岗位受影响会小一些,但有些岗位可能会受到 90%、95% 的影响。

Lenny Rachitsky还有一个你刚才没提到、但我在你第一次讲这个项目的帖子里看到的数据:今天增长最快的岗位里,有 70% 在一年前甚至都还不在岗位名单里。

Tomer Cohen对。增长最快的那些岗位,很多一年前根本不存在,更别说十年前、二十年前了。这个领域里其实有一整套都很惊人的数据。

Lenny Rachitsky好,那我们来聊聊你们做的这个项目。先告诉我们它叫什么,再讲讲它现在是什么样,以及你们希望它最终长成什么样。

Tomer Cohen好,我们叫它 full stack builder model。先说目标,永远先从目标说起。它的目标,就是让优秀的 builder 能把自己的想法做出来并推向市场,不受自己的岗位、技术栈,尤其是不受所在团队的限制。最终想实现的是,让这个 builder 能端到端地开发体验,把原本分散在不同领域里的技能和专业知识组合起来,整合到一起。它不是一串机械步骤,而是人和机器之间更流动的互动,这就是我理解的方式。你再回头看从 idea、insight 一直到 launch 的整个产品开发生命周期,我特别强调 builder 应该把时间花在哪里,也就是我认为优秀 builder 真正该发光的地方。

首先是 vision,也就是对未来有清晰而有吸引力的想象。其次是 empathy,这一点特别关键,要对未被满足的需求有深刻理解。communication 也很关键,现在你去看几乎所有岗位的招聘描述,都会写这一条,意思是你要能把别人拉到同一个想法上来。还有 creativity。对我来说,它意味着能想出超出显而易见答案之外的可能性。比如,我现在还不觉得 AI 特别擅长创造力。我觉得它很多时候更像是在把你原本不一定能想到的东西重新带回来,但还不是那种更高阶的创造力;那一层我觉得人类还是强得多。
而我认为 builder 最重要的特质,最终还是 judgment,也就是判断力。有人会把它叫做 test making,但说到底,就是在复杂、模糊的情境里做出高质量决策。其他事情我都在拼命自动化,真的非常拼命。再看结果,这不只是“你能多打几次门”这么简单,我觉得很多人会说“迭代速度会很快”,没错,但你真正给一个大组织带来的,是更敏捷、更能适应变化、也更有韧性的能力。它们能更好地穿越未来,能把变化的速度真正匹配上响应的速度。
我脑子里常用的一个类比是海豹突击队。你来训练时,大家都会学很多东西,彼此交叉受训,覆盖多个领域。真正专业化的,是 mission 本身;他们以小队形式运作,非常灵活,而且可以很快拼装起来。我觉得未来真正会赢的组织,应该就是这个样子。

Lenny Rachitsky好,那如果把它浓缩成一句话,这个想法是不是:有一个 builder,几乎独自走完整个产品开发流程。他有一个想法,然后做研究、看数据、做原型、设计、上线。大概就是这条路线,对吗?

Tomer Cohen对,但不一定非得是他自己一个人做。不是那种……我还是相信团队的。

Lenny Rachitsky明白,所以是更小的团队。

Tomer Cohen就是更小的团队。更小,而且更聚焦问题本身、聚焦 mission,而不是……举个例子,我们现在开始做 pods 这个概念。我们不再是大团队了,而是组一个团队,理想情况下由 full stack builder 组成。重点不再是“我能不能把工程、设计、PM 三个人凑在一起”,而是看能不能找到那些可以横跨多个环节的人,然后他们一起去解决某个问题,大概一个季度左右,之后我们再把这些人重新组合成不同的 pod。这就是我们现在在做的一个例子,实际上在速度上和团队的聚焦度、灵活性上,都已经看到了不错的效果。

Lenny Rachitsky而且感觉你们真正想修正的,是团队越来越臃肿之后,速度、适应性和灵活性被拖垮了。因为回到你最开始说的,变化现在来得太快了,那些还在按老方式做事的公司,真的没法竞争。

Tomer Cohen对。不是说你非得把这个模型打碎,我觉得模型本身就是坏掉的。只是现在变化的速度,逼着我们看清这一点。

Lenny Rachitsky好,那回到 builder 现在还要做的事情,以及你想自动化掉的事情。你刚才列的是 vision、empathy、communication、creativity 和 judgment。

Tomer Cohen对。尤其是后面那几个,我会把重点放在最后那个。要我说,最重要的特质是什么,我会说还是判断力,或者说 test making 的能力。

Lenny Rachitsky那在你想自动化的部分里,你们已经在哪些地方取得了很大成功?你觉得这条路会走向哪里?

Tomer Cohen对。我觉得可以拆开来看,而且我也觉得……如果你现在是一家创业公司,其实很多情况下你一开始就可以这么做。没有历史包袱,没有遗留代码,没有旧的组织结构要背着走。实际上我和很多 AI-native 的初创公司聊过,他们就是按 full stack builder 的方式在工作,这就是他们起步的方式。如果你是在我们这种规模、或者市场上很多其他大公司的环境里,那这几乎就像是一个新的生产函数和新的思维方式,你得把它搭起来。我们主要在做三件事:第一是平台,第二是工具和 agents,第三是文化。

先说平台。这是那种必须先投入的基础建设,只有把这个打好了,后面好处才会慢慢体现出来。拿我们来说,平台这部分就是重构所有核心平台,让 AI 能在上面推理。比如我们在做可组合的 UI 组件和 server-side 的配套能力,本质上是在为 AI 进入我们的体系做准备。所以你不能随便拿一个第三方工具来,指望它直接跑在 LinkedIn 的技术栈上。实际上,这也是我们最大的一个学习:直接拿来用,通常都不行。真的不行。你得把它接进来,再深度定制,几乎是和那些公司在 alpha 阶段一起配合,才能让它在内部真正可用。

Lenny Rachitsky所以从某种意义上说,这就是在重构代码库,让它更高效地和 AI 协作,对吗?

Tomer Cohen对,而且很多时候还包括跟那些公司一起调整他们那边的栈,让它也能适配我们的栈。

Lenny Rachitsky你说“那些公司”,是指像 Cursor 这样的开发 agent,还有其他类似工具,对吧?

Tomer Cohen对,也包括 Figma 这类设计工具。你也可以把设计系统当成另一类例子来看。但这必须是双向配合,因为它们不是……很多情况下,我们还没看到谁能拿个现成工具过来,就立刻很好地理解我们基于代码的设计系统和我们独特的上下文。

Lenny Rachitsky我顺着这个话题问一句,Figma 这点很有意思。你刚才的意思是不是说,Figma 导出和维护设计系统的方式,得变一变,才能更好地适配 AI?

Tomer Cohen它们首先得知道怎么跟我们的设计系统配合,而这件事其实很多公司都在做。代码这边也是一样。不是你把工具扔进来,它就能很好地对你的代码库做推理。我们试过了。我们现在正在搭一层东西,让它能做到这一点,不管是 Copilot、Cursor、Windsurf 还是别的工具。

Lenny Rachitsky明白。对,Copilot,微软的那个。我懂了,我懂了。好,所以这就是平台层。也就是说,你们得先做这笔投入,才能让 AI 在构建和这些工作里真的有效。

Tomer Cohen然后是工具层。工具层才是真正开始做 agents 的地方。我前面说过,我想把除了那五项能力之外的事情都自动化掉,所以我们正在为此做工具。这里同样是一样的逻辑:我不能随便拿一个外部工具来直接用。比如,我们最重要的一个工具就是 trust agent。对 LinkedIn 来说,信任特别重要。LinkedIn 里有很多别的地方没有的独特信任向量,所以我们必须把这些 know-how、上下文和信息底座都放进这个 agent 里。最后我们就自己做了一个 LinkedIn 内部的 trust agent。

Lenny Rachitsky那这个 trust agent 是做什么的?是在你可能暴露了不该暴露的信息时提醒你?

Tomer Cohen对。你写规格、提想法的时候,会先走一遍 trust agent,它会告诉你有哪些脆弱点、可能引入了哪些伤害向量,或者会因为这个功能引入哪些风险。我还特地让我们的 trust 负责人来做这个工具。所以每个领域的 craft 负责人,都会在做自己的 agent。比如,我们有一个给求职者的功能叫 Open to Work。如果你正在找工作,你就可以打开这个状态。

Lenny Rachitsky对,就是头像圈上那个小绿标。

Tomer Cohen没错。其实这是个很好的信号。我看到它带来了很多正面的结果,大家会互相帮忙,整个社区围绕这个功能也很活跃。但与此同时,它也带来了一个信任风险,因为你处于 open to work 状态。找工作的人,可能比其他人更容易成为诈骗目标。所以我们要提前想清楚,怎么把这些风险尽量挡在前面。我们把几年前的那个规格拿去过了一遍 trust agent。它不仅找到了我们一开始就意识到的问题,还找到了我们后来才发现的那些漏洞。这就是一个非常成功的例子。

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章节 04 / 08

第04节

中文 译稿已完成

Tomer Cohen这是一个例子。另一个例子是 growth agent。还是那句话,LinkedIn 的增长体系非常独特。实际上,我们有一支很强的增长团队,也形成了一套很成熟的增长流程。我们把过去积累下来的各种独特增长闭环、漏斗设计、历史实验,基本都喂进了这个 growth agent。现在你可以把自己的 spec 和想法丢给它,它不只是帮你把事情做得更好,还会直接判断你的想法到底有多好。这种东西你没法买现成的,它太贴近 LinkedIn 自己的语境了,所以我们在这上面投入了很多。现在有一支团队在用它,而且这个用途一开始我根本没想到,就是我们的 UXR,也就是用户研究团队。他们会用 growth agent 去判断:面对所有会呈现给会员的东西,哪一类最有增长机会、最值得优先做。这原本根本不在我们的规划里,但现在团队已经开始把这些判断都汇进这个 agent 里了。

再举一个例子,是我们的 research agent。这个 agent 训练时吃进了大量会员画像。你可以把它理解成,它知道“小企业主”“求职者”这类典型角色分别在想什么。而且它用的不只是通用世界知识,还包括我们过去做过的研究、不断流入的支持工单,所以它对 LinkedIn 场景下这些 persona 的理解相当到位。之前有个团队写了一份 spec,当时他们还不知道我们已经有了 research agent。我就让它站在“小企业主”的视角,去评估我们那份营销 spec,结果它给出的批评非常到位,某种程度上甚至让团队调整了方向,把注意力转向另外一些更值得投入的集成工具上。但问题在于,公司内部那一整片知识语料,平时其实很难有人真正看全。
还有一个例子,是我们的 analyst agent。它学的是怎样查询整个 LinkedIn graph,而这个图谱规模非常大。以前这类事情你得依赖 SQL 查询,或者依赖数据科学团队;现在你可以直接用 analyst agent。到目前为止,这些工具我都会把它们定义成 MVP+。接下来几个月,我们的目标是把它们更大范围地 rollout。这里说的 externally,其实是指在 LinkedIn 内部更正式地铺开。

Lenny Rachitsky不是要把它们做成新的产品线。

Tomer Cohen没错。

Lenny Rachitsky好,我现在问题很多。首先就是,你们到底是怎么做这些 agent 的?你们用的是什么平台?在 LinkedIn 内部做一个 agent,到底需要什么?全是内部工具,还是也会用第三方能力?

Tomer Cohen这个问题很好。我们确实试了很多工具。对这类以知识语料为核心的 agent,我们从 Copilot Enterprise 到 ChatGPT Enterprise 都在用。但到目前为止,最关键的部分其实还是我们自己的定制化,这也是我们看到增益最大的地方。包括在这些 agent 之上再做 orchestrator,因为你最终是希望 agent 之间能彼此协作的。比如 trust agent 应该和 growth agent 来回协同,而不是一个跑完了再轮到另一个,纯粹串行执行。为了做到这一点,我们内部做了很多工作。这也是为什么我一直说,这件事确实需要这个级别的投入。

还有一些场景,比如我们正在合作推进的 design agent。我们会和多家公司一起实验,想搞清楚到底哪个产品最适合我们。有意思的是,这里又有一个新的学习:不同团队会自然偏向不同产品。所以这也是我们之后必须解决的问题,要认真想清楚怎样把它收敛得更好。因为从根上说,我们其实是想把流程尽可能简化,但这个现象确实是一个很大的学习点,也影响了我们最终会用哪些工具、又该怎样把它们整合进来。

Lenny Rachitsky明白。所以你可能有一个很强的 Figma agent,但有些团队还是更想用别的设计工具。

Tomer Cohen对。我们试过 Figma、Subframe、Magic Patterns 等等,结果发现大家会根据自己的职能、当前看问题的视角,以及之前对某个工具的熟悉程度,倾向于不同工具。可从公司角度看,我显然不想同时养八个 design agent,所以我们最终还是得收敛到少数几个。我觉得这件事在很多领域都一样,因为很多 agent 看起来都在解决相似的最终目标,只是路径完全不同。你最后会发现,我不觉得会出现一个赢家通吃的局面,因为用户的起点不同,决定了什么工具在那个具体场景里最顺手。

Lenny Rachitsky很有意思。另一个我觉得很有启发的点是,你们在设计的这些 agent 都非常垂直,每个 agent 都只负责一类 job to be done。这是刻意的选择吗?你们有试过做一个“什么都懂”的超级 agent 吗?

Tomer Cohen最终我们会走向 orchestrator,会把这些能力真正编排起来。但现在之所以先拆成一个个 agent,是因为我们希望能更好地评估和衡量每个 agent 的表现。我也觉得这里确实有专业深度的问题。现在我们的搭法是,未来会把很多底层复杂性藏起来。你未必会知道背后有一个 trust agent。比如我们内部有个叫 product jammer agent 的东西,它对应的是我们内部的一套 product jam 流程。你看到的可能只是一个 product jam engine,而这个 product jam agent 会在背后调动其他 agent 一起工作。只是目前,我们还是先从这些 building blocks 开始,再往上搭统一的 orchestration layer。

Lenny Rachitsky从你前面的分享里,还有一个很有意思的点,就是你们很多投入都放在了产品开发流程的前半段,比如帮助大家把需求想对、把 trust 梳理清、把 product jam 跑起来、把已有研究调出来。我猜一个原因是,写代码这件事本来就已经被很多 AI 工具显著加速了。你讲讲,为什么投资会更多集中在这里?以及到目前为止,你们在哪些地方看到了最大的效果?

Tomer Cohen没错。我们在编码上的投入其实更早就开始了,那一块已经逐步跑顺了。我们基本把它分成两段:一段是从 idea 到 design,另一段是从 code 到 launch。后者已经拿到了很多关注,我们在那边也取得了一些很大的进展。从 coding agent,到我们所说的 maintenance agent,比如构建失败时它会替你处理,再到 QA agent,都属于这部分。实际上,我觉得现在接近 50% 的失败构建,已经是由 maintenance agent 处理掉的。

Lenny Rachitsky哇。也就是说,现在 build 挂了,不一定要工程师扑上去修,agent 会先接手?

Tomer Cohen对。你甚至还能先把咖啡喝完,再决定要不要自己回来重新处理。

Lenny Rachitsky这也太酷了。

Tomer Cohen但在我们启动这个项目之前,idea 到 design 这段几乎没怎么被系统性投入过。而这其实是很大一块工作量,也是很多质量真正产生的地方,至少在进入编码阶段之前是这样。我们的目标是把这套能力开放给所有人。也就是说,如果你是工程师,你也可以用流程前段的这些工具,让自己真正成为一个 full stack builder。

Lenny Rachitsky那从开始搭这件事,到你们真的能拉起第一支团队、开始做这些最初的 agent、后端能力、重构代码库这些工作,大概花了多久?

Tomer Cohen我是在去年年底内部正式宣布这件事的。真正开始推进时,前期更多是在搭团队、搭流程。那些 agent 的第一个 MVP,大概是在真正训练启动后的四到五个月做出来的。但如果只看纯粹投入的工作量,其实就是几个月的专注建设。很大一部分时间都花在把知识语料汇总起来、清洗干净。这也是一个很重要的经验:你不能简单地让它访问整个 drive,然后说“你自己去这个知识库里全盘推理”。它其实很不擅长判断哪些旧资料更重要,也不擅长给不同信息分权重。你得非常明确地想清楚,在什么场景下给它什么上下文,以及你希望它重点盯住哪一块知识库。甚至连“金标准样本”或“黄金案例”的清洗整理,都是我们最大的学习之一。直接让它对整个知识库自由推理,效果并不好。

Lenny Rachitsky这很合理。里面可能就有某个研究员对某件事有很强烈的个人判断,而你其实并不认同;但模型不会知道,它会把这些也当成“这是数据,这是事实”。

Tomer Cohen没错。而且它也不总能理解原始 spec 和最终成功之间的关联。你其实得自己搭这层逻辑。这件事很有意思:当你思考这些工具要怎么引进来时,你会发现不能只是“接进来”就完了。你得知道该喂它什么。而所谓“喂它什么”,不只是给权限。我看到很多人只盯着连通性和集成,这会让我想起十多年前那次经历。那时候我和别人一起重建 LinkedIn 的 feed,从零开始。我真的坐下来一条条筛,什么样的内容算 LinkedIn 上优质的职业帖子,什么不算。那花了好几个星期去做那套 golden sample。但最关键的,不是把所有数据都喂进去,而是把对的数据喂进去。

所以这件事确实需要投入。这也是我现在经常跟很多 CPO、COO 聊这个流程时会反复强调的:前期这笔工必须先下,后面收益才会出来。更广义地说,AI 其实也是这样。哪怕你第一次学用 Cursor,或者学设计工具,无论是 Figma、别的工具,还是 Lovable,你都要先愿意投入这些时间,之后才会开始明显感觉到自己的速度和质量一起上来。这个提升一定会来,但前提是你得先把那段投入期过掉。

Lenny Rachitsky本期节目由 Miro 赞助。每天都能看到新的头条,说 AI 要来抢我们的工作,这让很多人焦虑、害怕。但 Miro 最近的一项调查讲的是另一套故事:76% 的人相信 AI 能帮助他们把工作做得更好,但超过一半的人不知道该在什么场景里用它。于是 Miro 推出了 innovation workspace,一个把人和 AI 放进同一个共享空间里协作的平台,帮助团队真正把事情做出来。十多年来,Miro 一直在帮助团队把大胆想法变成下一个大东西。现在,他们正站在用 AI 加速产品上市的前沿,把 AI 和人的潜力结合起来。这个播客的很多嘉宾都会分享 Miro 模板,我自己也经常用它和团队一起做头脑风暴。尤其是团队协作时,Miro AI 可以把便签、截图这类非结构化信息,几分钟内整理成图表、产品 brief、数据表和原型。你不需要成为 AI 高手,也不用再切去学一个新工具。你已经在 Miro 画布上做的工作,本身就是 prompt。想让团队更顺畅地做出好成果,可以去看看 Miro:miro.com/lenny。

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章节 05 / 08

第05节

中文 译稿已完成

Lenny Rachitsky现在这个 pilot 处在什么阶段?规模大概多大?有多少团队在用?已经交付了哪些东西?给我们一个当下状态的感觉。

Tomer Cohen我不会说它现在已经覆盖了组织里非常高的比例,还远没到那种采样面很大的阶段。但现在已经有相当一部分团队在使用它,并持续给我们很多反馈。我们也看到了不少很好的例子。对我来说,这件事的收益可以理解成一个公式:实验数量乘以实验质量,再除以从 idea 到 launch 所花的时间。所以如果只看节省时间这件事,无论是 PM、设计师还是工程师,现在每周都已经能省下几个小时的工作量。无论是前面说的 analyst agent、快速原型,还是 product jamming 的体验,都贡献很大。从质量上看,我们也明显感觉到,对 insight 的讨论整体好很多了。顺便说一句,质量和时间有时是互相促进的:质量更高了,你反而不需要在一件事上花那么多时间。

所以这些效果我们已经在看到了。至于实验量,我不会说现在已经有很大比例的组织都在用,但这会在之后到来,因为我们还没有在内部正式 GA。接下来几个月,等所有东西准备好,这一步就会发生。不过现在我们已经看到,设计师和 PM 会直接从 Jira ticket 里捞 bug,自己推进处理,这在以前几乎没见过。而且现在大家的兴趣很强,几乎所有人都想加入。实际上,当前最大的压力反而是:人人都想拿到权限,人人都想用这些工具一起做。我们只是想先确保它们已经足够好,再把它们放给整个组织大规模使用。

Lenny Rachitsky那你们具体是怎么 pilot 的?是给一部分人开放这些 agent,他们还是按原来的工作方式,只是多了这些工具可用;还是说你们直接挑出一支团队,告诉他们“以后就这么工作”,然后再看结果?

Tomer Cohen这个问题也很好。现在基本上是这样:我们有一支核心团队,专门在整个 R&D 体系里搭 FSB track,也就是 full stack builder 这条线。与此同时,也有一些 pockets 和 pods 的团队在使用它。换句话说,我们会挑一些明确的区域,把工具开放给他们。前提条件是,他们必须给反馈。因为对我们来说,反馈本身就是回报的一部分,它会让工具变得更好。所以这不只是“给访问权限”而已。我们要的是那些真的会用的人。早期采用者本来就是会帮你把产品打磨得更好的人。所以现在我们主要是按 pod model 在推进。

Lenny Rachitsky所以它像是在一个更大的团队里,切出一个 pod,比如设计师、PM、工程师组成的小组,在里面试这套方式?有没有什么具体例子,比如 LinkedIn 哪一块业务已经在这么做?

Tomer Cohen有。比如我们最近刚上线了 Semantic People Search 和 Semantic Job Search,那支团队就用了其中一部分工具来辅助构建。很典型的一点是,那支团队里的 PM 已经能直接用这些工具搭自己的 dashboard,而不是等设计资源排进来。再比如有一支设计团队,这件事一开始其实是从他们的 manager 开始往下推的。我跟他们说的一句话是:“别等官方 GA,直接开始做,先主动靠上去。”现在我们已经看到那支团队的设计师开始自己提 PR,这以前是从来不会发生的。接着其他团队也会说,那我们也想这么干。所以现在它是以一种草根式的方式慢慢长出来的。当然,也有一些更正式的变化。我会说,最先发生正式转变的,其实是高层。

比如产品高管团队,我们已经从按职能分的 leader,比如设计、PM、BD 等,转向按产品领域负责的 leader。他们要横跨整条栈来工作,而且还要接受来自这些不同职能的 360 反馈,看看他们是否真的具备 full stack builder 的工作方式。另一边,我们也在 junior 端启动一个新项目,叫 Associate Product Builder Program。我们之前的 APM 项目到今年就结束了,从明年 1 月开始,我们会启动 APB 项目。新人进入 LinkedIn 后,我们会教他们在 LinkedIn 的语境里怎么写代码、怎么做设计、怎么做 PM。他们会经过一套相当严格的训练流程,然后加入这些 pod。之后我们会逐步把这个项目做大,让它也成为 LinkedIn 里一个有分量的组成部分。

Lenny Rachitsky哇,所以这可能就是 APM 项目的未来形态,只不过变成了一种 full stack builder 式的 APM 项目。

Tomer Cohen某种程度上是的。我们给这群人设计了一套非常棒的训练,我自己都想报名进去。而且这套训练不只是给他们用。我们也会把它当成一个样板,去思考之后怎样把这套能力推广到整个组织。我们的视角大概是:你也许技术底子很好,但你还不是一个真正意义上在公司体系里做工程的人;或者你有很好的设计感觉,但你还没在大规模组织里做过设计。那我们会在 LinkedIn 教你怎么做。而这套训练,后面也会大量用于整个公司的能力扩散。

Lenny Rachitsky好,所以你们现在有这些项目、这些 pilot、这些 pod。你前面说,你们判断要不要继续全面推广,看的就是实验速度、质量,再结合时间这个公式。

Tomer Cohen对,准确说是除以时间。

Lenny Rachitsky除以时间。明白。

Tomer Cohen对。

Lenny Rachitsky我知道现在还早,不过按你刚才说的,你们现在已经看到团队每周能省下几个小时,大概是这个量级,对吗?

Tomer Cohen对。而且我觉得最重要的其实是反馈。你可以把这件事理解成“像做产品一样做这套体系”。我们其实是在内部构建一个产品,所以你需要找一批早期采用者来试,拿他们的反馈。而这些反馈真的非常棒。事实上,在 LinkedIn,使用这套东西最多的,正是我们最顶尖的那批人才。来自他们的反馈非常惊人,因为他们也更愿意花时间去用、去提建议。无论是他们输出结果的质量、为了获得价值愿意投入的时间,还是他们想成为其中一部分、想把它做大做好的意愿,都非常强。所以现在很多兴奋感,其实就是来自他们怎么用,以及我们在他们身上看到的质量提升。我想再过六个月左右,更多组织会开始使用它,到时候你就会看到更明显的整体指标了。

Lenny Rachitsky这真是个很有意思的观察。表现最顶尖的人,反而从 AI 里拿到了最大的收益。因为一直以来都有个问题:AI 到底是让原本不那么强的人变强,还是让本来就很强的人变得更强?听起来更像是后者。

Tomer Cohen是的。某种程度上,这既让人意外,也不意外。以前我们做别的转型时我也见过类似情况。之所以说意外,是因为你当然希望更多人都能加入、都愿意靠过来。但顶尖人才往往有一种特质,就是会不断想把自己的 craft 打磨得更好,而且他们天然想站在构建方式的最前沿。我觉得我们现在看到的也是同样的事情。所以我一直跟团队说一句话:即便我们把所有工具都做出来,他们会不会用?我现在知道答案是不一定。光把工具给出去,并不足以让大家真的用起来。你必须搭激励机制、搭动机、搭示范案例,让大家看到别人已经成功了。

这点我在 LinkedIn 从 desktop company 向 mobile company 转型时也见过,非常像。这里的 change management 会是决定性的。我现在看到很多公司把自己的 agent 推出来,就默认组织自然会采用,但事情根本不是这样。会有一小部分人先用,那通常就是最前沿的 5% 人才,他们天然喜欢新工具、对变化有偏好。但绝大多数人,需要的是更完整的变革管理,你得认真设计他们怎么进入这个过程。而这一切最终都落在文化层面上。对我来说,这反而是最重要、也最值得花力气的一块。

Lenny Rachitsky对,这块我也很想展开聊。我完全能理解为什么很多人没时间管这件事,因为他们手头本来就有一堆要交付的东西,日程已经塞满了。现在你还要额外腾出时间去学一个短期内未必马上有回报的新工具,所以很多人就会说:“好好好,我回头再学,之后总会用的。”结果就一直没用。你刚才说的 culture,是我第一次看到你讲这件事时特别强调的第三个成功要素。前面有平台,也就是把代码库和环境准备好,让 AI 真能工作;然后有工具,也就是你说的这些 agents;再然后才是文化。在文化这一层,你能不能多讲一点,什么做法是真正有效的?我听到的一个点是,你们制造了一点稀缺感,好像不是所有人都能立刻拿到权限。还有什么办法,是真正把人带上船的?

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章节 06 / 08

第06节

中文 译稿已完成

Tomer Cohen这是一个例子。另一个例子是 growth agent。LinkedIn 在增长这件事上其实很特殊,我们有一支非常强的增长团队,也有一套很成熟的增长流程。过去积累下来的各种增长闭环、漏斗、实验方法,基本都被我们灌进了这个 growth agent。现在你可以把自己的思路、自己的方案丢给它,它不只是帮你把事情做得更好,还会直接判断你的想法到底好不好。这种东西你没法买现成的,它非常 LinkedIn,所以我们只能自己重投。现在有个用得特别有意思的团队,甚至一开始都不在我们的预期里,就是 UXR,也就是用户研究团队。他们会用 growth agent 去判断:面对会员端现在浮出来的这么多机会,到底哪一个最有增长潜力、最可能带来最大影响。这个用法我们一开始根本没想到,但现在各个团队都在把这类问题往这个 agent 里送。

再比如 research agent。它是按 LinkedIn 会员的不同 persona 来训练的,比如小企业主、求职者等等。它用的不只是通用世界知识,还吃进了我们过去做过的大量研究、以及持续流入的支持工单,所以它对“LinkedIn 场景里的这个人群”理解得相当到位。我们有一个例子是:某个团队写了一版 spec,但他们当时还不知道我们已经有 research agent 了。我就让 research agent 站在“小企业主”这个 persona 的角度,去评估那份营销相关的 spec,结果它的批评非常到位。某种程度上,它甚至直接把团队的方向带偏转了,转去关注另外一些更值得做的集成工具。但要让一个人天然看到公司内部这么大一整片知识语料,其实是很难的。
再举一个例子,我们还有 analyst agent。它是围绕“如何查询整个 LinkedIn graph”训练出来的,而这个图谱规模非常大。过去你可能要依赖 SQL 查询,或者去找数据科学团队帮忙,现在很多时候直接用 analyst agent 就行。到目前为止,这些工具我都会把它们叫做 MVP+ 阶段。接下来几个月,我们的目标是把它们正式铺开。这里说的 externally,其实是指在 LinkedIn 内部更大范围地推广。

Lenny Rachitsky不是把它们做成新的产品线往外卖。

Tomer Cohen对,没错。

Lenny Rachitsky好,我的问题一下子多起来了。首先就是,这些东西到底是怎么建出来的?你们是基于某个平台吗?在 LinkedIn 做一个 agent 需要什么?是全都用内部工具,还是也会用第三方?

Tomer Cohen这个问题很好。我们确实试了很多工具。像这类知识语料型 agent,我们从 Copilot Enterprise 到 ChatGPT Enterprise 都在用。但说到底,最重要的部分还是我们自己的定制化,这才是收益最大的地方。甚至包括在这些 agent 之上再做一层 orchestrator,因为你希望它们彼此能协同起来。比如 trust agent 应该和 growth agent 来回协作,而不是一个接一个按顺序串行执行。为了做到这一点,我们内部做了很多工作。所以我才会一直说,这件事确实需要真金白银的投入。

再比如 design agent 这块,我们同时在和多家公司合作,想弄清楚到底哪种产品最适合我们。有意思的是,这里也有一个新发现:不同团队会自然偏向不同产品。这件事后面我们还得继续收敛,认真想想怎么把它做对。因为我们的最终目标其实是尽量简化流程,但这个发现很重要,也直接影响我们到底选哪些工具、又怎么把它们整合进来。

Lenny Rachitsky明白。所以可能你有一个很强的 Figma agent,但有些团队还是想用别的设计工具。

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章节 07 / 08

第07节

中文 译稿已完成

Lenny Rachitsky明白。所以可能你有一个很强的 Figma agent,但有些团队还是想用别的设计工具。

Tomer Cohen对。我们试过 Figma,也试过 Subframe、Magic Patterns 等等。最后发现,大家会因为自己的职能、手头任务的可见性、以及过去对某个工具的熟悉程度,自然偏向不同工具。可从公司的角度,我并不想最后养出 8 个 design agent,所以我们还是得尽量收敛到少数几个。我觉得很多领域都会出现类似情况。因为这些 agent 虽然最终都想解决差不多的目标,但实现路径很不一样。你最后会发现,我不觉得这个市场会是“赢家通吃”,因为用户一开始站在哪个起点上,会很大程度决定某个工具在那个具体场景里到底有多顺手。

Lenny Rachitsky很有意思。另一个让我注意到的点是,你们在设计的 agent 都非常垂直,每个 agent 只负责一件 job to be done。这是一个很刻意的决定吗?你们有没有试过那种“什么都懂”的超级 agent?

Tomer Cohen最终一定会走向 orchestration,也就是有一层总 orchestrator 把它们串起来。但在一开始,我们还是希望能把每个 agent 的表现评估得足够清楚,知道它到底做得怎么样。而且不同领域确实有专业深度。现在我们正在按一种方式去搭,未来很多这些差异可以被藏起来。到时候你未必会知道背后有个 trust agent。比如我们内部有个叫 product jammer agent 的东西,它负责跑我们内部的 product jam 流程。你可能只是在用一个 product jam engine,但这个 product jam agent 背后其实会去联动其他 agent。只是眼下,我们还是先从这些基础积木开始,再慢慢把横向编排层搭起来。

Lenny Rachitsky你刚刚分享的另一个有意思的点是,你们大量投入都花在产品开发流程的前半段,比如帮团队把需求想清楚、把 trust 问题提前理顺、做 product jam、调用既有研究成果。我猜这可能也是因为写代码这块本来就已经被很多 AI 工具提速了。能不能讲讲,为什么投资重点会落在这里,以及你们目前看到最大效果的地方在哪里?

Tomer Cohen没错,编码这块我们很早就开始投了,而且已经逐步进入状态。我们基本把整个流程拆成两段:一段是从 idea 到 design,另一段是从 code 到 launch。后者已经得到很多关注,我们也在那边持续取得明显进展。从 coding agent,到我们说的 maintenance agent,比如构建失败了它会直接帮你处理,再到 QA agent,都是这个方向上的成果。事实上,现在接近 50% 的失败构建,已经是 maintenance agent 在处理了。

Lenny Rachitsky哇。所以现在如果 build 挂了,不一定是工程师自己跳进去修,而是 agent 先帮你修?

Tomer Cohen对,你甚至可以先把咖啡喝完,再回来重新看 build。

Lenny Rachitsky太酷了。

Tomer Cohen但在启动这个项目之前,我们在“idea 到 design”这段其实没有投入太多,而这恰恰是工作里非常重要的一段,也是质量很大程度上真正形成的地方,至少在你进入编码阶段之前是这样。我们的目标是把这套能力给到所有人。也就是说,就算你是工程师,也能在流程前端用上这些工具,真正成为一个 full stack builder。

Lenny Rachitsky那从开始搭这套东西,到你们能真正组出第一支团队、开始做这些初代 agent、以及一部分后端和代码库重构,大概花了多久?

Tomer Cohen我是去年年底在内部正式宣布这件事的,真正开始推进,是先把团队和内部流程搭起来。我记得第一批 agent 的 MVP,大概是在它真正成型后的四到五个月出来的。但如果只看集中投入本身,真正的硬工作差不多就是几个月。很多时间其实都花在把各类数据语料收拢起来、再清洗干净上。这也是一个很重要的学习:你不能只是把整个 drive 一股脑开放给它,然后说“来吧,在这整片知识库里自己推理”。它其实做得很差,既分不清过去哪些内容更重要,也不会很好地给信息加权。你得非常明确地设计:在什么场景下给它什么上下文、希望它聚焦哪一块知识。所以,连“清洗出一批 gold examples,也就是黄金样本”这件事,都成了我们最大的学习之一。直接让它在整个知识库上推理,这条路根本走不通。

Lenny Rachitsky对,这很合理。比如某个研究员可能对某件事有很强的个人观点,但你并不认同,agent 却会把它当成“这就是数据、这就是事实”。

Tomer Cohen没错。而且它也不一定能理解“原始 spec”和“最终成功”之间的关联。你得自己去搭这层关系。其实这件事很有意思。你会发现,把这些工具引进来,不是说接上就行了。你得知道你喂给它什么。所谓“喂”,也不是简单给权限。我看到太多人只盯着连通性和集成,觉得接上了就行。这让我想起十多年前,我和团队在 LinkedIn 从头重建 feed 的时候,我真的得自己一条条去筛:什么叫好的职业内容,什么不算。光整理出那一批黄金样本就花了好几周。但真正最重要的,从来不是把所有数据都塞进去,而是把对的数据塞进去。

所以这件事确实需要投入。我现在给很多 CPO、COO 讲这套方法时,都会强调这一点:前期这段苦活一定要做,后面才会有收益。我觉得这其实也是 AI 的一个普遍规律。哪怕你只是第一次认真学它,不管是 Cursor、Figma、别的设计工具,还是 Lovable,你都得先愿意投入那些小时数,之后你才会开始明显感受到速度和质量一起往上走。这个提升会来,但前提是你先投入。

Lenny Rachitsky本期节目由 Miro 赞助。每天都有新的新闻标题在吓我们,说 AI 会怎样抢走工作,让大家越来越焦虑、越来越不安。但 Miro 最近一项调研讲的是另一种故事:76% 的人相信 AI 能帮助他们把工作做得更好,但超过一半的人不知道该在什么时候用。Miro 推出的 innovation workspace,就是一个把人和 AI 放进同一工作空间里的智能平台,帮助团队把事情做成。十多年来,Miro 一直在帮团队把大胆的点子变成真正的产品;而现在,他们正站在让产品更快上市的前沿,把 AI 和人的潜力一起释放出来。这个播客的嘉宾也经常分享 Miro 模板,我自己也经常用它和团队一起 brainstorm。尤其是团队现在可以用 Miro AI,把便签、截图这类非结构化信息,几分钟内整理成图表、产品 brief、数据表格和原型。你不需要自己是 AI 专家,也不用再切去另一个工具。你已经在 Miro Canvas 上做的工作,本身就是 prompt。想让团队把工作做得更好,可以去 miro.com/lenny 看看。M-I-R-O.com/lenny。

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章节 08 / 08

第08节

中文 译稿已完成

我觉得,上次聊到这个话题时,我最常把它和……联系在一起。也许我不完全对,但我并不困惑,只是现在不太常这么说了。不过我很喜欢的一点是,成长型思维在我们家几乎像第二信仰。有一句话我特别喜欢:`becoming` 比 `being` 更重要。我觉得这和 FSB 模式有点呼应,因为你始终处在进度中、处在迭代中。重点不是抵达某个状态,而是旅程,是过程。你真正该爱上的,就是这个过程本身。要持续成长、持续演化,而且不带那种负面情绪,也没有什么 FOMO。它就是一件一直在发生的事。
如果一年后我回头看,我会问自己:我成长了多少?我学会了多少?为了把同样的事再做一遍,我又多了哪些技能?我在哪些地方变得更好了?我会不会觉得 2026 版的 Tomer 比 2025 版的自己更进一步了?差别在哪里?我挺喜欢这种想法。
Lenny 这正好引出我们的最后一个问题。等这期播客上线时,你离开 LinkedIn 14 年这件事也不再是秘密了,这段经历堪称传奇。你在被收购前很早就加入了,后来又帮他们完成整合。LinkedIn 14 年前被大家看待的方式,和今天已经完全不同。现在在那里,其实比很多人过去长期对 LinkedIn 的感觉要有意思得多。所以我想问的是,你现在是什么心情,接下来准备做什么?我猜你会接到很多人的电话,但你的打算是什么?
Tomer 是的,我现在更多是感到自豪。LinkedIn 这段旅程真的非常不可思议。我第一次真正深入了解 LinkedIn,是我搬到硅谷之后,2008 年去斯坦福听了一场关于社交网络的讲座,Reid 也在场。他讲的是把职业社区搬到线上这件事的力量。我当时特别 nerdy,觉得这个愿景太棒了,那会儿其实没打算加入,之后还自己创了公司。但机缘巧合之下,几年后我还是加入了,而且我真的觉得这个使命很了不起。从很多方面看,它都和我的人生目标很契合,能在这里经历这一切,真的太棒了。
我也非常感激。我最近跟公司也分享过,我开始从在这里的经历里提炼一些收获。很多收获都来自艰难时刻。LinkedIn 里有很多棘手的场面、艰难的决定、熬夜到很晚的时刻,但你从这些里学到的东西特别多,我真的非常感激。我也很兴奋。我就是很喜欢变化,也喜欢把自己放在一个能学到最多东西的位置上。现在正是最适合做东西的时候,所以我很期待去思考新的问题、新的领域,然后把接下来的十年投进去深耕。
Lenny 我觉得你要很久才能不再觉得自己还在为 LinkedIn 工作,也要很久才能把这些年一直在操心的事都忘掉。
Tomer 当你长时间在做一件事的时候,我想我和你也聊过,builder 最好的特质之一,就是对自己正在做的事变得非常投入。真的在乎。不是在乎那份工作本身,而是在乎产品本身。你会因为有人抱怨而感到痛,你会一直有种挥之不去的不满足感。对我来说,这有点像养孩子。所以是的,这很难,会一直很难。我永远都会把 LinkedIn 看作我亲手养大的孩子之一。
Lenny 那我很期待哪天你想明白下一步要做什么,或者开始做新的事情时,再请你回来。很高兴借这个机会更了解你。Tomer,非常感谢你今天来。
Tomer 我也很高兴能来,谢谢你,Lenny。
Lenny 各位再见。非常感谢收听。如果这期对你有帮助,欢迎在 Apple Podcasts、Spotify 或你常用的播客 App 里订阅本节目。也欢迎给我们评分或写一条评论,这真的很能帮助更多听众找到这个播客。你也可以在 lennyspodcast.com 找到往期所有节目,或者了解更多节目内容。我们下期再见。

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