In low-power wireless networks, every byte sent by an embedded device causes its radio to stay on a little longer, which eats into its limited energy reserve. And because the radio is often the most power-hungry circuit in the device, reducing the number of bytes to be sent and received automatically increases the battery lifetime of the device, resulting in a lower total cost of ownership for the end-user, hence better adoption. Low-power wireless devices tend to generate short data payload, typically in the order of 2-50 B. This means that protocol headers make up a large portion of the bytes inside a wireless frame, 30-70% is not uncommon. Compressing those headers, i.e. removing bytes that can be reconstructed anyways or that are not needed, makes perfect sense. This article serves as a primer on header compression in constrained networks. We start by describing exactly why it is needed, then survey the different standards doing header compression. We indicate how today’s approach requires expert input for every deployment, severely hindering the roll-out of such approaches. Instead, we argue that an automated approach based on machine learning and artificial intelligence is the right way to go, and provide blueprints for such approaches.