I've definitely seen this happen before too. Test-driven development isn't all that effective if the LLM's only stated goal is to pass the tests without thinking about the problem in a more holistic/contextual manner.
Reminds me of trying to train a small neural net to play Robocode ~10+ years ago. Tried to "punish" it for hitting walls, so next morning I had evolved a tanks that just stood still... Then punished it for standing still, ended up with a tanks just vibrating, alternating moving back and forth quickly, etc.
That's great. There's a pretty funny example of somebody training a neural net to play Tetris on the Nintendo entertainment system, and it quickly learned that if it was about to lose to just hit pause and leave the game in that state indefinitely.