Yes and with an incredibly large context and incredibly large domain specific knowledge.
We had an LLM based SRE product from a vendor I won't mention because we had an NDA as our management is sucking them off by trading whitepapers for discounts. It was like a drunk monkey with a wrecking ball. Think we had to pull it in under 2 weeks because it took out multiple production systems and lead to an entire cluster failover.
The meat sacks now know they have job security.
My experience is that SRE-esque work you experience the full range of model, from "wow, it would take us ages to even get to this theory for why something failed" to "well the priority field in this protocol goes from lowest=most important, but LLM wrote code as if it was highest=most important, so if someone actually pushed it to production the company wouldn't have working internet access any more".
And a lot of "wishing up a feature", I was using it to explore solutions for a given problem in too I didn't knew 100% and it pretty much came to same solution I wanted to do but... the capabilities were not there in the tool so it just started making up probable config clauses, and of course, it didn't work.
Even on simpler stuff there were traps, for example in middle of debug session I asked it to modify Gitlab config to add request duration logging, so it added correct config format to a flag that didn't exist (option was there, just under different name), because it didn't bother to read the docs (since then I generally link it the docs first so it doesn't try to remember and get it wrong).
All of that is both very dangerous, and also easily fixed by just having competent operator there. And as a tool it's great, as replacement it is just AI bros delusion