The issue with HATEOAS is a little overstated. You don't need a full AI with independent agency. What you need is a clear media type that corresponds to some

The issue with HATEOAS is a little overstated. You don't need a full AI with independent agency. What you need is a clear media type that corresponds to some domain concepts that both the client and server agree on. The client and server don't even have to totally agree, as long as there is some overlap. The server may provide functions that the client doesn't care about, and the client may care about functions that the server doesn't provide (but are provided by another server). Failure cases are: - media types totally disjoint (this wouldn't work for a human either, since the server couldn't do anything that the user wants to do with the resource) - media type misunderstandings - there is overlap in the functions, but what the client intends and what the server does are two different things, because their concept of that domain function is different (that would also be the same problem for a human) - media types undefined - everyone is just passing random unlabeled JSON globs, so any domain concepts have to be hardcoded equivalent on both sides (this is one case where a human might be able to intuitively guess the right thing, but only if their mental model happens to match the server's model) The solution is to document the domain concepts of the media types that fit your domain from both perspectives, find the places that don't overlap or match in name but not semantics, and decide what to do about them.