The ultimate vision for AI in product isn't just generating specs. It's creating a dynamic knowledge base where shipping a product feeds new data back into the system, continuously updating the company's strategic context and improving all future decisions.

The traditional, linear handoff from product (PRDs) to design to dev is too slow for AI's rapid iteration cycles. Leading companies merge these roles into smaller, senior teams where design and product deliver functional prototypes directly to engineering, collapsing the feedback loop and accelerating development.

The vision for Codex extends beyond a simple coding assistant. It's conceptualized as a "software engineering teammate" that participates in the entire lifecycle—from ideation and planning to validation and maintenance. This framing elevates the product from a utility to a collaborative partner.

Instead of a linear handoff, Google fosters a continuous loop where real-world problems inspire research, which is then applied to products. This application, in turn, generates the next set of research questions, creating a self-reinforcing cycle that accelerates breakthroughs.

The traditional PM function, which builds sequential, multi-month roadmaps based on customer feedback, is ill-suited for AI. With core capabilities evolving weekly, AI companies must embed research teams directly with customer-facing teams to stay agile, rendering the classic PM role ineffective.

To prevent silos, Apollo fosters a culture where employees spend time helping other teams, knowing the favor will be returned. This "flywheel" of mutual assistance is the core driver of their integrated model, cemented by firm-wide incentives like equity for all employees and bonuses tied to firm citizenship.

To avoid choosing between deep research and product development, ElevenLabs organizes teams into problem-focused "labs." Each lab, a mix of researchers, engineers, and operators, tackles a specific problem (e.g., voice or agents), sequencing deep research first before building a product layer on top. This structure allows for both foundational breakthroughs and market-facing execution.

The best products are built when engineering, product, and design have overlapping responsibilities. This intentional blurring of roles and 'stepping on each other's toes in a good way' fosters holistic product thinking and avoids the fragmented execution common in siloed organizations.

By embedding product teams directly within the research organization, Google creates a tight feedback loop. Instead of receiving models "over the wall," product and research teams co-develop them, aligning technical capabilities with customer needs from the start.