Pooling and Shape Arithmetic
A CNN's spatial resolution has to shrink somewhere between a 224×224 input and a single classification decision — pooling is the classic way to do that shrinking, trading spatial precision for a degree of invariance and reduced compute. Getting the resulting shapes right, at every layer, is the single most useful bookkeeping habit for building a CNN that actually runs.