You may be right on this
You may be right on this
I have seen hit or mixed results. For some very basic tasks I have been able to use [company approved "ai"] for some dev/ops/etc tasks and it did probably save me around 2-3 hours of extra work just by giving it error output and then checking the changes it suggested. I don't know if it will be worth the overall cost in the long term though. That is yet to be seen.
Humans are the most expensive part of your business for a reason. The "AI" is not good enough (yet) to fix prod problems at 3:00 AM that have never happened before.
Archive: https://archive.today/cR7gz
From the post:
>Nearly four decades ago, when the personal computer boom was in full swing, a phenomenon known as the “productivity paradox” emerged. It was a reference to how, despite companies’ huge investments in new technology, there was scant evidence of a corresponding gain in workers’ efficiency. Today, the same paradox is appearing, but with generative artificial intelligence. According to recent research from McKinsey & Company, nearly eight in 10 companies have reported using generative A.I., but just as many have reported “no significant bottom-line impact.”
I have seen hit or mixed results. For some very basic tasks I have been able to use [company approved "ai"] for some dev/ops/etc tasks and it did probably save me around 2-3 hours of extra work just by giving it error output and then checking the changes it suggested.
I don't know if it will be worth the overall cost in the long term though. That is yet to be seen.
Humans are the most expensive part of your business for a reason. The "AI" is not good enough (yet) to fix prod problems at 3:00 AM that have never happened before.
Archive: https://archive.today/cR7gz
From the post:
>>Nearly four decades ago, when the personal computer boom was in full swing, a phenomenon known as the “productivity paradox” emerged.
It was a reference to how, despite companies’ huge investments in new technology, there was scant evidence of a corresponding gain in workers’ efficiency.
Today, the same paradox is appearing, but with generative artificial intelligence. According to recent research from McKinsey & Company, nearly eight in 10 companies have reported using generative A.I., but just as many have reported “no significant bottom-line impact.”
(post is archived)