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Tomer Cohen

Episode #283

Chief Product Officer (CPO)

LinkedIn

👥Team & Culture🎯Product Strategy

📝Full Transcript

13,478 words
Lenny Rachitsky (00:00:00): I think it's so underappreciated, the turnaround that has happened within LinkedIn. I check it at least 10 times a day. What was the strategy behind it? Tomer Cohen (00:00:06): I start backwards. It's like what is the potential here? If you start from the premise that LinkedIn ultimately is a platform for economic opportunity that sits on top of a very strong social graph. Almost every aspect of economic transaction is possible. Lenny Rachitsky (00:00:20): Is there anything tactically that would just like, wow, that really made a big dent in people wanting to come here and post, share interesting content? Tomer Cohen (00:00:25): To really set the new purpose for it, which was this is not a springboard for other products. This is not a traffic jumpstart, it's not an upsell feed. It's really about people that matter, talking about things that I care about professionally. The first thing we did was really making AI first. Lenny Rachitsky (00:00:39): How do you actually on the ground help people shift their perspective and think AI first? Tomer Cohen (00:00:43): So it wasn't like, "Oh, we have this cool technology, what can we do with it?" It was like, "Let go of what you've built. Go back to the objectives you were trying to solve and now with this technology, how can you do that objective better?" Lenny Rachitsky (00:00:52): There's so much I want to dig into here. Is there anything else that you think would be interesting or useful for folks? Tomer Cohen (00:00:57): AI is the ultimate matchmaker. It's underutilized, it's misunderstood, it's really about... Lenny Rachitsky (00:01:07): Today my guest is Tomer Cohen. Tomer is chief product officer at LinkedIn overseeing all teams responsible for building and creating LinkedIn products and experiences, including product development, design, business development, content creation, and customer operations. During his tenure at LinkedIn, Tomer was head of the mobile team, led the effort t...

💡 Key Takeaways

  • 1Adopting the 'Wrong but not confused' mindset ensures team alignment and faster learning cycles.
  • 2Turnaround products ('Minus one to one') require isolating a test cohort (e.g., 2M users) to prove value without disrupting core business metrics.
  • 3In an AI-first world, PMs must shift from controlling the exact user flow to controlling the 'ingredients' (data, objectives, guardrails).
  • 4Product leaders must understand the 'engine' of AI: the objective function, features, and data collection strategy.
  • 5To integrate AI effectively, leaders should force a 'Diverge then Converge' process: wipe roadmaps clean, explore widely, then bet big on a few objectives.
  • 6A successful marketplace (like LinkedIn Feed) relies on 'Value Exchange' matching—ensuring the right content reaches the specific audience that values it professionally.

📚Methodologies (3)

👥 Team & Culture

A leadership philosophy that prioritizes clarity of thought and execution over the guarantee of correctness. By ensuring everyone is pulling in the exact same direction, the team can validate or invalidate hypotheses faster, whereas confusion (hedging) relies on luck for success.

Core Principles

  • 1.Clarity of Thought: Don't mask disagreement as misunderstanding. If you disagree, debate it; if you misunderstand, clarify it. Don't linger in between.
  • 2.Clarity of Execution: Align resources strictly to priorities. If your top talent isn't working on your top priority, you are confused.
  • 3.The Learning Requirement: You cannot learn from a mistake if the execution was confused. You must commit fully to a path to know why it failed.

"We might be wrong, but we are not confused."

#'wrong#confused'#protocol
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🎯 Product Strategy

A strategy for revitalizing products with negative momentum. It involves envisioning the ultimate potential ('The Mountain Peak') rather than iterating on the status quo, and using isolated cohorts to prove the new model works before scaling.

Core Principles

  • 1.Start Backwards from the Peak: Don't look at current metrics. Ask 'What is the potential here?' (e.g., millions of professionals sharing knowledge).
  • 2.The Cohort Carve-Out: Isolate a statistically significant group (e.g., 2 million users) to serve as a 'separate country'. Optimize their experience without worrying about the main org's metrics.
  • 3.Value Exchange over Volume: Shift the metric from raw clicks/traffic to 'Matchmaking'. Does the creator get professional value? Does the consumer get knowledge?

"This is not a springboard for other products... It's really about people that matter, talking about things that I care about professionally."

#'minus#turnaround#strategy
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🎯 Product Strategy

A framework for building AI products where the PM shifts from designing rigid steps to curating the data and objectives. The PM provides the ingredients and guidelines, and the AI (the chef) cooks the dish (the experience) for the user.

Core Principles

  • 1.Control Ingredients, Not the Dish: You don't define the exact flow. You define the data, the safety guardrails, and the objective function.
  • 2.Diverge then Converge: When new tech arrives, wipe the roadmap. Allow teams a period of 'chaos' to explore creatively, then rigorously converge on top strategic bets.
  • 3.PMs Must Own the Engine: PMs cannot treat AI as a black box. They must define the algorithm's objective function, feature sets, and data collection strategy.

"You don't control the experience anymore, you control the ingredients."

#ai-first#'chef#ingredients'
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