Loop it. Use another agent (from a different company helps) to review the code and documentation and call out any inconsistencies.
I run a bunch of jobs weekly to review docs for inconsistencies and write a plan to fix. It still needs humans in the loop if the agents don’t converge after a few turns, but it’s largely automatic (I baby sat it for a few months validating each change).
That might work for hallucinations, that doesn't work for useless verbose. And the main issue is that LLM don't always distinguish useless verbose from necessary one, so even when I ask it to reduce verbose, it remove everything save a few useful comments/docstring, but some of the comments that were removed I deemed useful. Un the end I have to do the work of cutting verbose manually anyway.
Who to believe?
I listened to the US broadcast, definitely dampened, I'm not sure if it's a default filter or one that triggers with the broadcaster, it is extremely likely it isn't intentional. My Bayesian ass is 95% sure.