AI presentation tools need a controllability layer, not just better first drafts

A lot of AI presentation discussion still focuses on first-draft quality. Can the model make a deck from a prompt, notes, a doc, or a transcript. That matters, but I think it is becoming the less interesting part of the problem. The bigger issue is controllability after generation. A presentation is not just a set of slides. It is a sequence of claims, evidence, pacing, emphasis, and visual hierarchy. When a user asks for a revision, they often do not want a new deck. They want a narrow intervention inside an existing structure. That is hard for current systems because the editing target is not always a text span. It might be a section of the narrative, a layout choice, the relationship between two slides, or the level of detail in one supporting point. If the system can only respond by regenerating a broad chunk, it risks damaging parts the user already accepted. For AI slide tools, I suspect the next useful layer is not just better templates or prettier layouts. It is a way to represent the deck so the user can make local changes with predictable boundaries. Keep this section. Rewrite this claim. Split this slide. Change this visual treatment. Do not touch the rest. The first draft gets attention because it is easy to demo. The second pass is where usefulness shows up.