When I hear "ChatGPT says..." on some topic at work, I interpret that as "Let me google that for you, only I neither care nor respect you enough to bother confirming that that answer is correct."

It is no different than charging me for a channel package full of content I don't watch, cancelling my favorite shows, flooding their channels with unscripted reality garbage, or using "stunning" and "so-and-so just did such-and-such" on nominally serious news web sites. If I don't like it I can choose not to participate, but if I do choose to participate, I agree to accept whatever is offered to me; my opinion was neither requested nor required. So if the top three linear TV news providers chooses to go with an AI-based newsreaders that people initially don't like... so what?

"The data that on-air personalities are too expensive?" It doesn't seem to me , for the purposes of this conversation, that identification of a cost center required a quantitative analysis. The cost of human talent is non-zero, presumably large enough to merit scrutiny, and unpredictable; that is sufficient, to my way of thinking. So is the cost of the equipment and infrastructure to capture and transmit video image of that human talent, and the humans who maintain and operate that infrastructure.

We've seen several decades of human cost-reduction initiatives, across multiple industries and fields of endeavor, so I'm taking that as evidence that if there is a cost that can be reduced or removed, someone somewhere is looking at doing so. Everything from assembly-line automation, to switching to email over inter-office memos and mailrooms, to the abandonment of fixed-benefit pensions, to self-service kiosks in fast-food restaurants, demonstrates that costs will be cut where they can be cut.

They wouldn't have off-air scandals, require insurance, pensions, teams of wardrobe and makeup artists, security details; They wouldn't need to travel. And that is just the on-air talent. You can replace thousands of tv studios all over the world with a handful of workstations and compute power.

Because I have wired trackballs from both Logitech and Kensington, and have for many years. You can pry my Kensington Orbit from my cold, dead hand.

Is this what LinkedIn considers radical candor?

My own experience with LLM-based coding has been wasted hours of reading incorrect code for junior-dev-grade tasks, despite multiple rounds of "this is syntactically incorrect, you cannot do this, please re-evaluate based on this information" "Yes you are right, I have re-evaluated it based on your feedback" only to do the same thing again. My time would have been better spent either 1) doing this largely boilerplate task myself, or 2) assigning and mentoring a junior dev to do it, as they would only have required maybe one round of iteration.

Based on my experience with other abstraction technologies like ORMs, I look forward to my systems being absolutely flooded with nonperformant garbage merged by people who don't understand either what they are doing, or what they are asking to be done.