LinkedIn's Chief Product Officer on Growing to 1B Users with AI | Tomer Cohen
Plus Tomer's favorite principles for building AI products, how to land your dream job on LinkedIn, and more
Dear subscribers,
Today, I want to share a new episode with Tomer Cohen, CPO of LinkedIn.
Tomer gave me an inside look at the key drivers behind LinkedIn’s growth to 1B+ users. He also shared his best advice for building AI products and advancing your PM career. Finally, I had to ask him about humor and r/LinkedinLunatics 🙂
Watch now on YouTube, Apple, and Spotify.
Tomer and I talked about:
(00:00) 3 must-have principles for building AI products
(02:55) Revamping LinkedIn’s feed for knowledge-sharing
(06:15) Why it's so hard to be a feed PM and how Tomer overcame doubts
(11:09) r/LinkedInLunatics and the role of humor
(13:18) How newsletters and videos can thrive on LinkedIn
(18:24) "Thinking fast and slow" as an AI PM
(24:49) "Founder mode" and traits that the best PMs have
(27:52) Designing a PM org to reward impact instead of optics
(31:29) How to land your dream job
Keep reading for the takeaways.
How LinkedIn grew to 1B+ users by building an incredible content feed
Welcome Tomer! I think people often underestimate LinkedIn’s scale. Can you start by sharing some high level stats with us?
I joined more than a decade ago when we had less than 100M members. Now we're well north of 1B members and continue to grow. Every minute on LinkedIn, people:
View 1.5M feed posts
Watch 140 hours of learning content
Make 13,000 connections
You can really see that exchange of economic opportunity across the platform, whether it's knowledge sharing, jobs, or building your business.
LinkedIn used to be a place where people just updated their resume instead of consuming content. How did this transformation happen?
The key change was the feed.
We had more of an activity feed (e.g., who changed jobs) before we decided to make it the ultimate matchmaker between those who have knowledge and those who seek it.
It’s hard being a feed PM because there’s so much scrutiny on it – if you make one little change, another team’s product metrics could tank. How did you manage this?
It wasn’t easy! We did it in 3 steps:
We built a dedicated feed team. Multiple teams were working on feed which hurt the cohesiveness of the product. So the first thing we did was to make it one team.
Updating the objective function. The feed’s objective was sending traffic to other products based on click through rate, which is very shallow. We moved away from CTR to conversation starters (e.g., comments, replies) for knowledge sharing.
Learning and iterating. The problem with conversation starters is that they can be abused by spammers. So we went deeper into downstream actions on if people were building meaningful connections and conversations. Our objective function became a composite of different metrics as a result.
It’s so hard to get the objective function right. For example, on X, I think the feed optimized for time spent. But that has led to all these viral videos and memes polluting the content. How did you find the right balance for LinkedIn’s feed?
You hit the nail on the head. I think the most important job of an AI-first product leader is to:
Think fast and slow about the objective of your algorithm.
Let me explain: