We present a safe-by-design trajectory planning and tracking framework for nonlinear dynamical systems using a hierarchy of system models. The planning layer uses a low-fidelity model to plan a feasible trajectory satisfying the planning constraints, and the tracking layer utilizes the high-fidelity model to design a controller that restricts the error states between the low- and high-fidelity models to a bounded set. The low-fidelity model enables the planning to be performed online (e.g. using Model Predictive Control) and the tracking controller and error bound are derived offline (e.g. using sum-of-squares programming). To provide freedom in the choice of the low-fidelity model, we allow the tracking error to depend on both the states and inputs of the planner. The goal of this article is to provide a tutorial review of this hierarchical framework and to illustrate it with examples, including a design for vehicle obstacle avoidance.