I recently ran into two baffling, what felt like GPT 3.5 era completely backwards misinterpretations of an unambiguous sentence once each in Codex and CC/Sonnet a few days apart in completely different scenarios (both very early in the context window). And to be fair, they were notable partially as an "exception that proves the rule" where it was surprising to see but OP's example can definitely still happen in my experience.

I was prepared to go back to my original message and spot an obvious-in-hindsight grey area/phrasing issue on my part as the root cause but there was nothing in the request itself that was unclear or problematic, nor was it buried deep within a laundry list of individual requests in a single message. Of course, the CLI agents did all sorts of scanning through the codebase/self debate/etc in between the request and the first code output. I'm used to how modern models/agents get tripped up by now so this was an unusually clear cut failure to encounter from the latest large commercial reasoning models.

In both instances, literally just restating the exact same request with "No, the request was: [original wording]" was all it took to steer them back and didn't become a concerning pattern. But with the unpredictability of how the CLI agents decide to traverse a repo and ingest large amounts of distracting code/docs it seems much too over confident to believe that random, bizarre LLM "reasoning" failures won't still occur from time to time in regular usage even as models improve given their inherent limitations.

(If I were bending over backwards to be charitable/anthropomorphize, it would be the human failure mode of "I understood exactly what I was asked for and what I needed to do, but then somehow did the exact opposite, haha oops brain fart!" but personally I'm not willing to extend that much forgiveness/tolerance to a failure from a commercial tool I pay for...)