I think the argument is more about the historical data structures that were used in rich text. A lot of editors either used the DOM, or a very flattened data structure like Google Wave, Quill.js, DraftJS etc. With these flattened data structures it becomes harder to represent complex rich text with things like tables, nested blocks, etc. If you have a nice JSON data structure that is collaborative you can do a lot, and in many / most use cases it is sufficient. However, you can run into use cases where the collaborative data structure will ensure consistency across clients, but violate some semantic constraint on the data.
For example, imagine you have an application that has a list that must contain at least one element. Assume there are two elements in the list. A Shared JSON data structure on its own (that allows for immediate local edits) would to allow two clients to simultaneously delete one element each. The end result is that the client app on both sides will become aware that the constraint was violated only when the remote operation comes in. Resolving this becomes difficult. What is the resolution strategy? Which of the two clients should initiate it? This is a contrived example for sure. But you run into things like this in various use cases, and occasionally you need either new data structures that encode these semantics, or you need an extendable system that allows you to customize constraints, and resolutions.
For example, imagine you have an application that has a list that must contain at least one element. Assume there are two elements in the list. A Shared JSON data structure on its own (that allows for immediate local edits) would to allow two clients to simultaneously delete one element each. The end result is that the client app on both sides will become aware that the constraint was violated only when the remote operation comes in. Resolving this becomes difficult. What is the resolution strategy? Which of the two clients should initiate it? This is a contrived example for sure. But you run into things like this in various use cases, and occasionally you need either new data structures that encode these semantics, or you need an extendable system that allows you to customize constraints, and resolutions.
That said, you can get pretty far with just JSON!