>It's not different from other things like databases, GPU drivers, 3D engines for games, etc.
Not quite the same. E.g. databases are a part of the system itself. It's actually pretty helpful for a SWE to understand them reasonably deeply, especially when they're so leaky as an abstraction (arguably, even the more nuanced characteristics of your database of choice will influence the design of your whole application). AI/LLMs are more like dev tooling. You don't really need to know how a text editor, compiler or IDE works.
We have a service at work which categorizes internal documents and logs, then triggers some automation depending on the category. It processes maybe 100 per day. Previously we only used some combination of metadata, regex, and NLP to categorize. Now a call to a LLM is part of that service. We save a lot of manual time where we used to have to resolve unknown documents. The LLM can help fill out missing data, too. It's all stored as annotations so it's clear who/what edited the data.
Granted this is a pretty simple task and a low stakes scenario, but I don't think we should limit ourselves to assuming AI will always only be dev tooling.
Not quite the same. E.g. databases are a part of the system itself. It's actually pretty helpful for a SWE to understand them reasonably deeply, especially when they're so leaky as an abstraction (arguably, even the more nuanced characteristics of your database of choice will influence the design of your whole application). AI/LLMs are more like dev tooling. You don't really need to know how a text editor, compiler or IDE works.