Response surface methods provide a principled way of finding experimental conditions that optimize a response. They are based on sequential experimentation where we alternate between locally exploring the changes in response around a given condition and determining a set of conditions that likely yields increasing response values. We consider central composite designs as a family of flexible experimental designs for exploration and building approximate models of the surface in the vicinity of a given condition. We illustrate these techniques using a real-life example, where we optimize the composition of a growth medium for yeast.