Podcast Summary

Podcast: Lenny's Podcast: Product | Career | Growth
Episode: Why LinkedIn is turning PMs into AI-powered "full stack builders” | Tomer Cohen (LinkedIn CPO)
Date: December 4, 2025
Host: Lenny Rachitsky
Guest: Tomer Cohen, Chief Product Officer, LinkedIn

Overview

In this episode, Tomer Cohen, CPO at LinkedIn, discusses a groundbreaking organizational and product development transformation at LinkedIn: the introduction of the Full Stack Builder (FSB) model. This approach, deeply grounded in enabling human + AI collaboration, aims to dissolve traditional functional boundaries and empower individuals to take products from ideation to launch—regardless of their original expertise or role. The conversation explores the rationale for this seismic shift, tactical implementation, cultural challenges, the role of specialized AI agents, and what it takes to future-proof both organizations and careers in a world where 70% of job skills are projected to change by 2030.

Key Discussion Points and Insights

1. The Urgency of Change in Product Development ([00:00]–[09:47])

• The landscape is shifting fast:

  • By 2030, 70% of the skills needed for today’s jobs will change. Even if you’re not changing jobs, your job is changing.
  • Organizational “process complexity” over the years has led to micro-specialization and slow, bloated product development cycles.
  • Quote:
    • “Change is happening faster than we’re able to respond to it.” (Tomer Cohen, [05:34])
    • “To stay competitive, you have to go back to some first principles… and reimagine what it means to be building.” (Tomer Cohen, [05:34])

• LinkedIn’s perspective:

  • Using proprietary data, LinkedIn sees new job types emerging at unprecedented speed. 70% of this year’s fastest-growing jobs weren’t even on last year’s list. ([11:28])
  • The product development lifecycle became needlessly complex—research, design, code, launch, iterate—had been decomposed into exhaustive sub-steps and specializations.

• Opportunity and necessity:

  • The emerging AI toolset enables companies to collapse these "stacks"—returning to craftsmanship, empowerment, and a focus on high-judgment, creative, cross-disciplinary work.

2. The Full Stack Builder (FSB) Model ([12:02]–[15:56])

• Definition & Goal:

  • The FSB model empowers any talented builder to bring an idea to life, blending skills across what were traditionally distinct domains.
  • Key Traits Expected of Builders:
    • Vision, Empathy, Communication, Creativity, and most critically, Judgment.
    • “...what I think is the most important trait for a builder is judgment...making high quality decisions in complex, ambiguous situations.” (Tomer Cohen, [16:16])

• From Big Teams to Nimble Pods:

  • Organize talent into small, mission-focused pods (akin to Navy SEAL cross-training).
  • Emphasizes adaptability, speed, and resilience over rigid function-based teams.
  • Quote: “It’s not that we have to break the model. The model is broken. It’s just this pace of change is helping us realize it.” (Tomer Cohen, [15:56])

3. Automation and the Role of Specialized AI Agents ([16:27]–[29:03])

• Automating Everything Except Core Human Strengths:

  • AI agents target everything except vision, empathy, communication, creativity, and judgment.

• Three Pillars for Implementation:

  • 1. Platform:

    • Re-architecting codebases and design systems so AI can reason over them. Off-the-shelf AI tools rarely work on complex, legacy systems without heavy customization.
    • Quote: “You have to bring it in and customize a lot of it working almost in alpha mode with those companies...” (Tomer Cohen, [18:12])

  • 2. Tools & Agents:

    • Creating deeply specialized agents:
      • Trust Agent: Assesses vulnerabilities and trust concerns in specs and ideas specific to LinkedIn’s user base ([19:35]).
      • Growth Agent: Critiques and optimizes growth strategies, trained on years of internal growth tactics.
      • Research Agent: Learns from all LinkedIn user research, support tickets, and persona data to give nuanced feedback.
      • Analyst Agent: Lets any builder query LinkedIn’s immense data graph without SQL/data science expertise.
    • These “agents” often outperform generic tools and must be tightly integrated and sometimes orchestrated to collaborate seamlessly.

  • 3. Culture:

    • Change management is central; rolling out tools is not enough. Incentives, role modeling, and celebration of early adopters are key drivers.

4. From Experimentation to Rollout ([31:48]–[38:12])

• Pilot Structure and Early Results:

  • Currently running as pilots within "pods"—cross-functional groups experimenting and providing feedback.
  • Measuring Success:
    • The metric: Experimentation Volume x Quality / Time from Idea to Launch
    • Early signs: PMs, designers, and engineers save several hours per week, quality of insights has improved, and top performers are the quickest adopters.
    • Quote: “The feedback from [top talent] has been incredible...the quality of their output, the time they're spending to get value back, their desire to ... make this even better...” ([37:34])

• Training the Next Generation:

  • The traditional APM (Associate Product Manager) program is being replaced by an Associate Product Builder track. New joiners are trained in coding, design, and PM skills, then rotate through FSB pods.

5. Change Management & Cultural Adoption ([38:12]–[47:29])

• Top Talent Leads the Charge:

  • Early and most effective adoption comes from those already striving to improve at their craft—innovation and use spreads from their successes.
  • Quote: “If we build all those tools, will they use it? ... You have to build the incentives, the motivation, the examples...” (Tomer Cohen, [38:24])

• Cultural tactics:

  • Celebrate and broadcast wins
  • Use exclusivity/FOMO to spur interest
  • Integrate use of AI/FSB competencies into hiring and performance reviews ([41:23])
  • Explicitly grant permission to innovate—don’t wait for a reorg, try it now
  • Share tools openly and encourage peer-to-peer sharing and learning

6. Challenges and Lessons Learned ([48:00]–[55:26])

• Technical/Organizational Hurdles:

  • Off-the-shelf AI tools almost never work without robust customization—especially given the legacy data and code at scale.
  • Feeding the right training/corpus material to agents is more important than just “access to all the data.”
  • Tool adoption is bumpy; people gravitate toward what they know even if different from the “ideal” tool stack.

• Not Everyone Needs to Be Full Stack:

  • Specialization retains value, just less than before. System builders empower full stack builders, with a smaller number of hyper-specialists than in the past.

• Titles, Paths, and Mindset:

  • “Full Stack Builder” now exists as a career track at LinkedIn. Success is more about mindset than formal title.
  • Quote: “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.” ([45:20])

7. Career, Personal Reflection, and Advice ([51:44]–[56:43])

• Upside for Talent:

  • It’s easier than ever to transition between functions (e.g., design → PM → FSB). AI lowers the barrier to lateral and upward moves.
  • Quote: “The incentives for you are so aligned with the organization of what we’re asking for...” (Tomer Cohen, [52:10])

• Advice for Adopters:

  • Start with platform, tools, and culture together—not just one. Culture is what makes the transformation stick.
  • If launching a similar transformation:
    • Share progress early and often—even when working with a small team.
    • Be patient; invest upfront to see compounding benefits later.
    • Don’t wait for formal approval or reorgs; empower action at every level.
  • Quote: “Whether 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.” ([55:26])

Notable Quotes & Memorable Moments

• “By 2030… skills required to do your job… will change by 70%. So whether or not you’re looking to change your job, your job is changing.”
  — Tomer Cohen, [00:00]

• “Change is happening faster than we’re able to respond to it.”
  — Tomer Cohen, [05:34]

• “The goal is to empower great builders to take their idea and to take it to market… It’s really a fluid interaction between human and machine.”
  — Tomer Cohen, [12:02]

• “I want to automate everything outside of those five traits [vision, empathy, communication, creativity, judgment].”
  — Tomer Cohen, [16:16]

• “If we build all those tools, will they use it? … You have to build incentives, motivation, the examples... Otherwise they won’t.”
  — Tomer Cohen, [38:24]

• “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.”
  — Tomer Cohen, [45:20]

• “The incentives for you are so aligned with the organization of what we’re asking for.”
  — Tomer Cohen, [52:10]

• “Do not wait... Focus on the progress you’re making. Over-communicate… If you’re inside your org, and I would say whether or not your CPO or CEO is announcing this program, go do it or join an organization that does it….”
  — Tomer Cohen, [55:26]

Timestamps for Key Segments

• The Coming Job/Skills Revolution: [00:00]–[09:47]
• What is the Full Stack Builder Model? [12:02]–[16:27]
• Automating via Specialized AI Agents: [16:27]–[29:03]
• Pilot Program Structure & Early Results: [31:48]–[38:12]
• Culture & Change Management: [38:12]–[47:29]
• Challenges & Not Everyone Goes Full Stack: [48:00]–[49:45]
• Career Paths, Mindset, and Advice: [51:44]–[56:43]
• Tomers's Departure & Career Reflections: [64:12]–[66:53]

Concluding Thoughts

This episode offers a compelling vision for how AI isn’t just a layer on top of product development—it should fundamentally reshape how organizations work, removing friction and unleashing creativity and adaptability. LinkedIn’s model, as described by Tomer Cohen, is likely a harbinger for the broader shift coming to all knowledge work. Whether you are a leader or an individual builder, the takeaways are clear: embrace tools thoughtfully, invest in cultural transformation, and start experimenting with "full stack" approaches now—because the future won’t wait.

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