With AI assistants reading hundreds of papers to provide summaries, users no longer need to engage with original content. This forces publishers to redefine where their value lies, moving away from direct consumption metrics towards the quality of their underlying data for synthesis.

Unlike traditional software that optimizes for time-in-app, the most successful AI products will be measured by their ability to save users time. The new benchmark for value will be how much cognitive load or manual work is automated "behind the scenes," fundamentally changing the definition of a successful product.

In an agentic world, the core AI model becomes a commodity. The defensible product is the curated experience layer built on top of it—the guardrails, instructions, and personality that define the user interaction and differentiate the offering.

The audience for marketing content is expanding to include AI agents. Websites, for example, will need to be optimized not just for human users but also for AI crawlers that surface information in answer engines. This requires a fundamental shift in how marketers think about content structure and metadata.

Many AI applications focus on content generation (e.g., chatbot answers). The deeper value lies in enabling content consumption: creating actionable insights that help users make better and faster decisions. Product managers should prioritize building features that provide decision support, not just information.

AI agents are becoming the dominant source of internet traffic, shifting the paradigm from human-centric UI to agent-friendly APIs. Developers optimizing for human users may be designing for a shrinking minority, as automated systems increasingly consume web services.

As consumers use AI for discovery, brand marketing must shift from human-centric storytelling to distributing structured information aimed at AI retrieval agents. These bots prioritize raw data over narrative, with the AI itself creating the story for the end-user post-ingestion.

When users consume content through an AI intermediary, traditional metrics like page views and scroll depth become meaningless. Publishers must now measure value by tracking API calls, how often their data informs an AI's answer, and whether users click attribution links back to the original source.

As foundational AI models become commoditized, the key differentiator is shifting from marginal improvements in model capability to superior user experience and productization. Companies that focus on polish, ease of use, and thoughtful integration will win, making product managers the new heroes of the AI race.