How LinkedIn became interesting: The inside story | Tomer Cohen (CPO at LinkedIn)

What was the main strategy behind LinkedIn's feed transformation?

The revamp of LinkedIn's feed was a strategic masterpiece anchored on three key pillars: embracing AI, defining a distinct purpose, and emphasizing professional content.

First, LinkedIn set its sights on becoming AI-first. By integrating AI deeply into the core team, they aimed to enhance matchmaking between content and users. This shift wasn't merely about using advanced technology but about rethinking objectives and employing AI to meet those goals effectively. With a unified approach, AI became the engine driving content personalization and engagement.

Next, the feed's purpose was redefined. It transitioned from being a mere platform for promotional content and upsells to a space focused on people that matter, discussing professionally relevant topics. This deliberate focus on meaningful interactions marked a significant departure from its previous state, emphasizing quality over quantity in user engagement.

To solidify this transformation, LinkedIn concentrated on professional content. The platform encouraged users to share expertise and engage in knowledge transactions, making it a hub for professional growth and economic opportunities.

By combining these elements, LinkedIn's feed evolved into a highly engaging, knowledge-driven platform, setting itself apart in the social media landscape.

How did LinkedIn implement an AI-first mindset?

Implementing an AI-first mindset at LinkedIn required multiple strategic steps.

First, the company established an AI academy to train every product manager (PM) on the fundamentals of artificial intelligence. This initiative mirrored their earlier push to make LinkedIn mobile-first, ensuring comprehensive education and alignment across the organization.

Focusing on objectives was another critical step. Product teams were continually challenged to define the objectives of the algorithm, laying out clear goals and success metrics for every AI feature. This rigorous approach ensured that AI-driven initiatives were not just about technological novelty but were strategically aligned with business goals.

Moreover, LinkedIn proactively integrated AI into its core teams. They broke down the silos between AI experts and product developers, creating cohesive teams where AI was a driving force in every project. This integration allowed for more seamless collaboration and innovation, enhancing the overall product quality.

By weaving AI into the fabric of their product development process, LinkedIn ensured that AI was not just an add-on but a fundamental part of their strategy.

What were the key tactics used to make the feed more engaging?

• 2 Million User Carve-Out Experiment
  A subset of 2 million users was isolated to test new feed features without disrupting overall metrics. This approach allowed for iterative development and fine-tuning before broader implementation.

• Focus on Professional Content
  The cornerstone of the strategy was transitioning the feed's purpose to highlight professional content. This shift encouraged users to share expertise, thereby creating a knowledge-driven platform.

• AI-Driven Content Matching
  Leveraging AI, the platform prioritized showing users relevant posts from professionals. This was achieved by directly integrating AI experts into product development teams, ensuring seamless content personalization.

• Redefined Feed Objectives
  The team moved away from treating the feed as a promotional tool. Instead, it aimed to become a hub for professionally meaningful interactions, prioritizing quality over volume.

• AI Academy for Product Managers
  An internal AI academy was created to upskill product managers in AI fundamentals. This initiative ensured that AI was understood and effectively utilized across all teams.

These tactics collectively transformed LinkedIn's feed into an engaging, professional space.

How did Tomer Cohen's leadership contribute to LinkedIn's success?

Tomer Cohen's leadership at LinkedIn has been pivotal in the company's transformation. His guiding mantra, "We might be wrong, but we are not confused," emphasizes clarity and conviction over perfection. He believes in setting ambitious goals and aligning the entire team towards these objectives.

Cohen's focus on clarity ensures that everyone pulls in the same direction, reducing confusion and increasing efficiency. Rather than getting bogged down in being right, he encourages a unified approach towards common goals. This principle has allowed LinkedIn to innovate rapidly and stay ahead in a competitive landscape.

Moreover, his rapid career progression within LinkedIn—from Senior PM to Chief Product Officer—showcases his deep understanding of product leadership. He recognized early on the potential of the LinkedIn feed and championed its transformation through strategic decisions such as carving out 2 million users for focused experimentation. His ability to see the big picture and drive AI-first strategies contributed significantly to LinkedIn's engagement and professional content focus.

These qualities make Tomer Cohen's leadership style a model for product managers looking to make impactful changes within their organizations.

What lessons can product managers learn from LinkedIn's feed transformation?

1. Set Ambitious Goals Aim high. LinkedIn envisioned a feed where millions of professionals would engage daily. This ambitious vision guided their strategic decisions and innovations.

2. Foster an AI-First Culture Integrate AI into the core of your product. Create training programs like LinkedIn's AI academy to ensure that every team member understands and can leverage AI effectively. Make AI a key part of the development process, from setting objectives to defining features.

3. Allow Room for Experimentation Encourage your teams to explore different solutions. LinkedIn's 2 million user carve-out experiment allowed for innovation without disrupting overall metrics. This controlled testing environment led to significant insights.

4. Focus on Clear Objectives Ensure that every team member knows the goals of each algorithm or feature. Clarity in objectives helps in creating a unified direction and reduces confusion within the team.

5. Iterate and Learn Carve out spaces for continuous learning and iteration. LinkedIn continuously fine-tuned their AI and content strategy, learning from each iteration to improve user engagement.

These practices, emphasizing ambitious goal-setting, fostering an AI-first mindset, and allowing for experimentation, provide a robust framework for product managers aiming to drive significant change within their organizations.