Product teams developing artificial intelligence (AI) increasingly create solutions with societal consequences and ethical implications. However, they often lack the ability to anticipate or mitigate ethical risks during development, relying primarily on legal compliance review and ex-post accountability. To address this challenge, this paper proposes that product teams can learn from structured ethical oversight procedures, well-established in healthcare, defense, and other high-stakes domains. Guided by this logic, we introduce the Sprint Ethics Board (SEB), a lightweight governance framework that adapts established committee models to agile workflows in product teams. The SEB is defined by three features (1) clear trigger points tied to product milestones, (2) a core group of members—product decision authority, ethical and domain expertise, and an external stakeholder advocate—that together form the minimum credible quorum for oversight, and (3) artefacts—a one-page Ethics Brief and a machine-readable Decision Log—that integrate into the sprint toolchain in product development. Together, these features enable the SEB to satisfy regulatory demand and move toward trustworthy AI in product development. The paper offers a design framework and outlines a research agenda to evaluate the SEB empirically in industry contexts. By suggesting how ethical review procedures can be translated into agile decision-making in product teams, the SEB reframes ethics oversight from a retrospective safeguard into a proactive, enforceable, and auditable function of product delivery. If adopted, the SEB framework can serve as a firm foundation for Ethical AI development.