Plan and lead a large recommendation project

You're presented with a recommendation design scenario, but the interviewer cares more about leadership and execution than about detailed modeling. Describe how you would:

1. Convert a high-level recommendation concept into an execution plan, covering milestones, dependencies, and risks.
2. Estimate staffing: which roles are needed (for example, MLE, DS, backend, product, design, data engineering) and roughly how many people.
3. Lay out a realistic timeline with phased rollout, and explain how you would coordinate across functions.
4. Define success metrics and describe how you would run experiments.
5. Manage trade-offs, disagreements, and stakeholder communication.

Overview: This behavioral and leadership question tests leadership, execution planning, cross-functional coordination, resourcing, and stakeholder communication in the setting of machine learning recommendation product development.