I believe there will always be some amount of navigation of the latent space required, and people who don’t understand how to navigate it will struggle.
To use your analogy, even if the horse is tame you still need to know how to ride it.
Can you code? Can you illustrate? Can you build? Piece by piece, you sketch, implement, hone, finetune, improve, retry, go into detail, expand... The ease of the process is relative to the tools adopted.
Of course there has to be knowledge behind it. Of course you have to know your tools. But "wild horse" and "diligent consultant", axe and scalpel require different degrees areas and modalities of competence.
A well built tool will build on the competences already natural for the professional (e.g. a graphic designer will be able to sketch and to instruct the machine in a reasonably standard language). Of course the better you know your tool, the greater the effectiveness. But currently, the systems can be strongly unreliable - they do not respect the request.
The user will have to learn to deal with a machine taking natural language as an input just like any manager has to know how to speak to personnel to obtain what is wanted. On the other hand, the implementation of "virtual personnel" which is reliable is a responsibility of the tool developers.
It seems like you agree based on parts of your comment like "A well built tool will build on the competences already natural for the professional".
Communicating to another entity (even a human) “exactly what you had in mind” (or, more to the point, so as to get them to behave so as to produce “exactly what you had in mind”) is a skill which involves understanding of the audience, understanding of the mode of communication, and understanding of the field about which you are communicating. “Prompt engineering” is just a fancy name for the particular application of that set of skills in the domain of getting desired results out of an LLM. Whether or not the terminology ends up being durable, the skill isn’t going away, as long as we are using language to communicate with models.
(Once we get the ability to just plug our brain into an AI, will their be a skill of focussing properly so that the mind-reading tech reads the right thoughts? Probably, and that will be the new “prompt engineering”.)
There is a world of difference between the needs in governance in just having to write "Those decorations where I marked the area, make them a bit more Hans Holbein as opposed to Klimt", compared to knowing patching tricks so that if you asked the engine to draw a 'T' you were not being served a 'B'.
This latter example - ask 'B', get 'T' - I have seen from Midjourney only a few hours ago, in the public showcase. I have examined several prompts and results, and very often they do not overlap but very partially - the engine is like a wild horse.
That this is not intrinsic, but just a current stage, is only part of the story: the user will want to have a tool that allows the production of what the artist had exactly in mind (not just "anything nice as /inspired/ by our suggestions"). It is the normal form of the product in its "ready for shipment" state.