@carnage4life an alternate framing:
Getting good at using generative AI means using a tool that produces incorrect output 10% - 50% of the time. Such tools used to be rejected as not fit-for-purpose / not production-ready.
Many smart people struggle with this because they either
1 Get frustrated with being required to use a tool that’s not fit-for-purpose and having to expend time & energy fixing its incorrect outputs.
2 Decide to say “fuck it” and use it anyway because “management said so” and they have no genuine agency to stop or derail the train.
Both would have been considered reasonable positions only a few years ago and quite common.

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Endgame for the Open Web


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