Why LinkedIn is turning PMs into AI-powered "full stack builders” | Tomer Cohen (LinkedIn CPO)
Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Podcast Summary
In this compelling episode, LinkedIn CPO Tomer Cohen reveals how the company is pioneering the "Full Stack Builder" program—a radical new approach to product development that fully embraces what AI makes possible. (04:42) With 70% of job skills expected to change by 2030 and the fastest-growing jobs today not even existing a year ago, Cohen explains why traditional product development processes have become too complex and slow for today's pace of change. (06:25) LinkedIn has scrapped its traditional Associate Product Manager program, replacing it with an Associate Product Builder program that teaches coding, design, and PM skills together, while introducing a formal "Full Stack Builder" career ladder that enables anyone from any function to take products from idea to launch.
- The episode explores LinkedIn's transformation from traditional siloed product development to an AI-powered model that prioritizes speed, adaptability, and cross-functional capability
Speakers
Tomer Cohen
Tomer Cohen is the longtime Chief Product Officer at LinkedIn, where he has spent fourteen years helping transform the platform from a static networking site into the engaging professional platform it is today. He joined LinkedIn before its Microsoft acquisition and has been instrumental in major initiatives including the company's transition from desktop to mobile and now its pioneering Full Stack Builder program. Cohen recently announced his departure from LinkedIn after this legendary run to pursue new challenges in the rapidly evolving AI landscape.
Lenny Rachitsky
Lenny Rachitsky is the host of Lenny's Podcast and author of Lenny's Newsletter, one of the most influential product management publications. He previously worked as a product manager at Airbnb and has become a leading voice in the product management community, interviewing top leaders and sharing insights on building great products.
Key Takeaways
Embrace AI as Essential Infrastructure, Not Optional Tools
Cohen emphasizes that companies must completely reimagine their technology platforms to work with AI rather than simply adding AI tools on top of existing systems. (17:53) LinkedIn discovered that off-the-shelf AI tools never work immediately on enterprise code bases—they require extensive customization and platform re-architecture to be effective. This means building composable UI components and server-side architecture specifically designed for AI reasoning, working closely with AI tool companies in alpha mode to ensure compatibility with existing tech stacks.
Focus Human Energy on High-Value Creative Work
The Full Stack Builder model centers on five core human capabilities that remain irreplaceable: vision, empathy, communication, creativity, and judgment. (12:36) Cohen's philosophy is to automate everything else, allowing builders to focus on what humans do best—making high-quality decisions in complex, ambiguous situations and coming up with possibilities beyond the obvious. This approach recognizes that while AI excels at processing information and executing defined tasks, human judgment and creativity remain the key differentiators in product development.
Build Specialized Agents for Company-Specific Expertise
Rather than relying on generic AI tools, LinkedIn has invested heavily in building specialized agents that understand their unique business context. (19:35) Their trust agent incorporates LinkedIn-specific vulnerability vectors, while their growth agent is trained on the company's unique loops, funnels, and historical tests. These agents don't just execute tasks—they critique ideas and identify blind spots that teams might miss, often catching issues that weren't discovered until much later in traditional processes.
Top Performers Drive AI Adoption Most Aggressively
Contrary to expectations that AI would level the playing field, Cohen observed that their highest-performing talent are the ones using AI tools most extensively. (36:52) These top performers have an innate drive to continuously improve their craft and stay at the cutting edge of how they build. This insight suggests that AI may actually amplify the advantages of great talent rather than democratizing capabilities, making it crucial for organizations to focus change management efforts on helping all team members develop AI fluency and agency.
Culture Change Requires Systematic Incentive Alignment
Technology and tools alone are insufficient for transformation—culture change is the most critical component. (40:03) Cohen learned from LinkedIn's desktop-to-mobile transformation that successful adoption requires updating performance reviews, hiring criteria, and promotional pathways to reflect new expectations. This includes making AI fluency part of performance evaluations, celebrating wins publicly, creating exclusive access to drive FOMO, and ensuring leaders model the behavior they want to see across the organization.
Statistics & Facts
- 70% of the skills required to do current jobs will change by 2030, meaning regardless of whether people are looking to change jobs, their jobs are changing around them. (06:25)
- The fastest-growing jobs today are growing by north of 70% compared to last year's fastest-growing jobs, with 70% of today's fastest-growing jobs not even existing on job lists a year ago. (06:41)
- LinkedIn's maintenance agent now handles close to 50% of all failed builds automatically, allowing engineers to "finish their coffee" before needing to address build issues manually. (27:10)
