The need for emotional connection isn't limited to consumer products. All software is used by humans whose expectations are set by the best B2C experiences. Even enterprise products must honor user emotions to succeed, a concept termed 'Business to Human'.

Shift focus from the physical object to the process it enables. Whether for surgery, labs, or logistics, successful product development requires deeply understanding and improving the underlying workflow. The specific technology is secondary to a system design that correctly supports the process.

A platform's immediate user is the developer. However, to demonstrate true value, you must also understand and solve for the developer's end customer. This "two-hop" thinking is essential for connecting platform work to tangible business outcomes, not just internal technical improvements.

In businesses blending services and tech, the "product" is the entire package of technology, services, and expertise delivering a client outcome. This redefines product management’s scope beyond just the application to the holistic customer experience and the results it generates.

The traditional product team structure is evolving as roles blend. Product managers might write requirements that directly generate code, and design will become more central. The focus will shift to a unified 'builder' identity that values cross-functional craft and agility over rigid role definitions.

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.

The concept of 'product' now includes all customer-facing business units. Comcast designs and manages its sales processes and internal agent applications with the same rigor as its consumer apps, ensuring a cohesive experience by orchestrating all customer touchpoints as a single, unified product.

Leveraging AI requires a dual focus. Leaders must apply AI to solve genuine customer problems, not just for the sake of technology. Simultaneously, they must upskill their teams and re-engineer internal development processes to reduce handoffs and accelerate the entire product cycle.

The proliferation of AI has dramatically reduced development time, shifting the primary constraint in product delivery from engineering capacity to the customer's ability to learn and integrate new features into their workflow. More output no longer guarantees more value.