Читать книгу Habit Machine. AI Product Management - Ар'лан ис'Дрекхэм - Страница 33

Once the product exists, data prevents waste and forces ruthless prioritization. A backlog should never be driven by the loudest voice in the room. It should be driven by measurable impact.

— Tie every roadmap item to a behavioral or business metric. If a task can’t plausibly improve Time-to-First-Value, Day-7 Retention, or conversion, question why it’s being prioritized.

— Measure the effect of every release. A feature isn’t successful because it shipped. It’s successful if it moves the intended metric without degrading adjacent flows.

— Use staged rollouts and feature flags. Release to small cohorts, monitor error rates and engagement shifts, then expand or roll back based on evidence, not optimism. [Research: Google SRE staged rollout practices; modern feature flag telemetry studies].

Common mistakes: prioritizing based on internal preference over observed impact, measuring success by story points completed instead of behavioral shift, assuming a shipped feature is automatically a good feature. Shipping is not proof. Retention is.