Saying 'no' to product ideas is often contentious. At GitHub, the process is simplified by first 'seeking the truth'—rigorously assessing if an initiative aligns with the team's definition of success. If it doesn't, the 'no' becomes an objective, logical conclusion rather than a subjective or political decision.

Instead of choosing between diverse user segments, GitHub defines success with extreme clarity. This allows them to treat prioritization like an investment portfolio, allocating dedicated squads to different user needs (e.g., open-source maintainers vs. enterprise admins) to achieve a balanced outcome.

Engineering often defaults to a 'project mindset,' focusing on churning out features and measuring velocity. True alignment with product requires a 'product mindset,' which prioritizes understanding the customer and tracking the value being delivered, not just the output.

To keep growth aligned with product, foster a shared culture where everyone loves the product and customer. This isn't about formal meetings, but a baseline agreement that makes collaboration inherent. When this culture exists, the product team actively seeks marketing's input, creating a unified engine.

Effective product development starts with internal alignment. Using exercises like Instagram's "Stories Mad Libs" creates a shared, candid understanding of the product's current state. This "organizational therapy" is a prerequisite for overcoming team biases and conducting successful user research.

To serve both solo developers and large enterprises, GitHub focuses on creating horizontal "primitives" and APIs first. This foundational layer allows different user types to build their own specific workflows on top, avoiding the trap of creating a one-size-fits-none user experience.

Instead of siloing roles, encourage engineers to design and designers to code. This cross-functional approach breaks down artificial barriers and helps the entire team think more holistically about the end-to-end user experience, as a real user does not see these internal divisions.

A prototype-first culture, accelerated by AI tools, allows teams to surface and resolve design and workflow conflicts early. At Webflow, designers were asked to 'harmonize' their separate prototypes, preventing a costly integration problem that would have been much harder to fix later in the development cycle.

To bridge cultural and departmental divides, the product team initiated a process of constantly sharing and, crucially, explaining granular user data. This moved conversations away from opinions and localized goals toward a shared, data-informed understanding of the core problems, making it easier to agree on solutions.