By creating a central repository infused with company strategy and market data, AI tools can help junior PMs produce assets with the same contextual depth as a 20-year veteran, democratizing product intuition and standardizing quality across the team.

Block is re-architecting its entire business by treating all functions—from payments to HR—as a collection of capabilities. These are unified and accessed through a central AI agent middleware layer (Goose), orchestrating workflows across previously siloed product and corporate functions.

Stripe avoids costly system rebuilds by treating its new payments foundation model as a modular component. Its powerful embeddings are simply added as new features to many existing ML classifiers, instantly boosting their performance with minimal engineering effort.

Stripe's AI model processes payments as a distinct data type, not just text. It analyzes transaction sequences across buyers, cards, devices, and merchants to uncover complex fraud patterns invisible to humans, boosting card testing detection from 59% to 97%.

The most exciting application of AI in partnerships isn't automation but its ability to analyze data and reveal non-obvious trends and correlations. This allows leaders to see patterns in partner performance and customer behavior that are invisible to the naked eye.

View AI less as a tool for discrete tasks and more as the foundation for a central marketing hub. This system uses AI to create and maintain branded playbooks for all marketing activities, ensuring consistency and quality regardless of who is executing the work.

Stripe’s payments model shows how AI creates powerful data flywheels. Their massive, proprietary transaction dataset trains superior models, which improves the product, attracts more customers, and widens their data advantage, making it nearly impossible for new competitors to catch up.

The primary value of AI app builders isn't just for MVPs, but for creating disposable, single-purpose internal tools. For example, automatically generating personalized client summary decks from intake forms, replacing the need for a full-time employee.

A key competitive advantage wasn't just the user network, but the sophisticated internal tools built for the operations team. Investing early in a flexible, 'drag-and-drop' system for creating complex AI training tasks allowed them to pivot quickly and meet diverse client needs, a capability competitors lacked.