Eugene Yan's latest mailbag post addresses a common but thorny question: how should a new data team lead define the team's vision and roadmap? The piece is framed as a direct response to a reader who is stepping into a leadership role and wants to avoid drifting without clear direction.
Yan's approach is practical rather than academic. He treats vision-setting as a leadership skill that can be learned, and he likely walks through considerations like aligning with business priorities, understanding stakeholder needs, and translating high-level goals into a concrete plan. Because the source is a single practitioner's perspective, it doesn't offer a consensus view—but it does provide a grounded starting point for anyone facing the same challenge.
For AI and ML teams specifically, the question of vision and roadmap is especially relevant, as these teams often struggle with balancing exploratory work against product-driven deliverables. Yan's advice, while not AI-specific, offers a template that can be adapted to the unique pressures of machine learning projects.