AI doesn't replace creative experts; it elevates their role. Their craft shifts from manually creating individual assets to designing and building robust, reusable AI systems that empower the entire organization to generate on-brand content.

Users who treat AI as a collaborator—debating with it, challenging its outputs, and engaging in back-and-forth dialogue—see superior outcomes. This mindset shift produces not just efficiency gains, but also higher quality, more innovative results compared to simply delegating discrete tasks to the AI.

Finding transformative AI use cases requires more than strategic planning; it needs unstructured, creative "play." Just as a musician learns by jamming, teams build intuition and discover novel applications by experimenting with AI tools without a predefined outcome, letting their minds make new connections.

Early AI adoption by PMs is often a 'single-player' activity. The next step is a 'multiplayer' experience where the entire team operates from a shared AI knowledge base, which breaks down silos by automatically signaling dependencies and overlapping work.

Shift your view of AI from a passive chatbot to an active knowledge-capture system. The greatest value comes from AI designed to prompt team members for their unique insights, then storing and attributing that information. This transforms fleeting tribal knowledge into a permanent, searchable organizational asset.

It's a common misconception that advancing AI reduces the need for human input. In reality, the probabilistic nature of AI demands increased human interaction and tighter collaboration among product, design, and engineering teams to align goals and navigate uncertainty.

Effective prompt engineering isn't a purely technical skill. It mirrors how we delegate tasks and ask questions to human coworkers. To improve AI collaboration, organizations must first improve interpersonal communication and listening skills among employees.

Instead of asking an AI for a single answer, Reid Hoffman advocates for "role prompting"—creating a team of AI agents with different expert perspectives (critic, historian, etc.). This simulates a board of advisors and represents a shift from individual contribution to managing AI teams.

The next frontier for AI isn't just personal assistants but "teammates" that understand an entire team's dynamics, projects, and shared data. This shifts the focus from single-user interactions to collaborative intelligence by building a knowledge graph connecting people and their work.