Why LinkedIn is turning PMs into AI-powered "full stack builders” | Tomer Cohen (LinkedIn CPO)

This moment turns the interview's larger thesis into a concrete operating example. The source passage is: “When 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.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

The exchange is useful because it exposes the practical trade-off behind the proposal. The source passage is: “You're experimenting with a very different way of building product at LinkedIn that fully embraces what AI unlocks.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

Here the conversation moves from an abstract claim to evidence from LinkedIn's work. The source passage is: “We 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.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

This passage adds an important qualification to the interview's argument. The source passage is: “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.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

The speakers use this detail to make the model more specific. The source passage is: “Change 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.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

This moment turns the interview's larger thesis into a concrete operating example. The source passage is: “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?” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

The exchange is useful because it exposes the practical trade-off behind the proposal. The source passage is: “Top talent has this tendency of continuously trying to get better at their craft. The key trait that I'm emphasizing for builders is...” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

Here the conversation moves from an abstract claim to evidence from LinkedIn's work. The source passage is: “Today, 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. (00:02:06): A huge thank you to Shira Gasarch for suggesting topics for this conversation. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It helps tremendously. And if you become an annual subscriber of my newsletter, you get a year free of a bunch of incredible products, including a year free of Devin, Lovable, Replit, Bolt, n8n, Linear, Superhuman, Descript, [inaudible 00:02:29], Gamma, Perplexity, Warp, Granola, Magic Patterns, Raycast, ChatPRD, Mobbin and Stripe Atlas. Head on over to lennysnewsletter.com and click product pass. With that, I bring you Tomer Cohen after a short word from our sponsors. (00:02:42): My podcast guests and I love talking about craft and taste and agency and product market fit. You know what we don't love talking about? SOC 2. That's where Vanta comes in. Vanta helps companies of all sizes get compliant fast and stay that way with industry-leading AI, automation, and continuous monitoring. Whether you're a startup tackling your first SOC 2 or ISO 27001 or an enterprise managing vendor risk, Vanta's trust management platform makes it quicker, easier, and more scalable. Vanta also helps you complete security questionnaires up to five times faster so that you can win bigger deals sooner. The result? According to a recent IDC study, Vanta customers slashed over $500,000 a year and are three times more productive. Establishing trust isn't optional. Vanta makes it automatic. Get $1,000 off at vanta.com/lenny. (00:03:36): This episode is brought to you by Figma, makers of Figma Make. When I was a PM at Airbnb, I still remember when Figma came out and how much it improved how we operated as a team. Suddenly, I could involve my whole team in the design process, give feedback on design concepts really quickly, and it just made the whole product development process so much more fun. (00:03:56): But Figma never felt like it was for me. It was great for giving feedback and designs, but as a builder, I wanted to make stuff. That's why Figma built Figma Make. With just a few prompts, you can make any idea or design into a fully functional prototype or app that anyone can iterate on and validate with customers. Figma Make is a different kind of vibe coding tool. Because it's all in Figma, you can use your team's existing design building blocks, making it easy to create outputs that look good and feel real and are connected to how your team builds. Stop spending so much time telling people about your product vision, and instead show it to them. Make code-backed prototypes and apps fast with Figma Make. Check it out at figma.com/lenny. (00:04:42): Tomer, thank you so much for being here and welcome to the podcast.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

This passage adds an important qualification to the interview's argument. The source passage is: “Thank you. It's great to be back.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

The speakers use this detail to make the model more specific. The source passage is: “It'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?” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

This moment turns the interview's larger thesis into a concrete operating example. The source passage is: “It 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%. (00:06:25): 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? (00:07:11): 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. (00:07:58): 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. (00:08:41): 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. (00:09:26): 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.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

The exchange is useful because it exposes the practical trade-off behind the proposal. The source passage is: “Wow. 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.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

Here the conversation moves from an abstract claim to evidence from LinkedIn's work. The source passage is: “To do their current job.” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.

This passage adds an important qualification to the interview's argument. The source passage is: “To do their current job. And what is this looking at? Is this just based on historical data or how do you find that?” Read as part of the surrounding discussion, it shows that the change depends on deliberate choices, not on the tool alone.