What just came to my mind is that the current main selling point of AI, is coder productivity. Some anecdotal experiences from a small agile team:

We had 1 week sprints and our PO had sometimes trouble to prepare enough work for the next sprint. We had 4 week sprints and we often ended up pulling tickets from the next sprint. There was often a mismatch in pace. (Quite funny, the time we had found a balance, management ordered all teams to have the same sprint lengths. They couldn't deal with all the asynchronous, overlapping sprint starts/ends. They choose to forfeit our productivity for theirs.)

So productivity isn't all about coders, it's also about owners / managers / shareholders supplying work. This kind of work is much about communication with several involved parties and researching usecases and features in a very specific context. LLMs can help with parts of it, but at one point there will be a flood of excessive, unverified generic reports and LLMs that again condense them with all the inaccuracies, that managers/owners may drown in a fuzzy mess of LLM bureaucracy. Nuances and importance will get lost in excess.

We often had rather large stories that simply had a small set of bulletpoints, because we already communicated everything in person and they were just reminders for the most important stuff. The importance here is that this reflected the teams agency how we solve things. An LLM can probably not at all provide that currently, as they are always excessive and try to add "helpful" details. They simply cannot pick up social norms and agreements, and prompting them correctly is in my opinion very hard or too time consuming.

LLM assisted coding or vibe coding is all the hype. But I have the feeling that the big realization sets in once all supporting processes are convoluted with AI noise, the peers that used to collaborate are detached and social conflicts and misunderstandings escalate.