Chapter 1: What is the main topic discussed in this episode?
Smart, sharp, and slightly unhinged. Late night's fresh perspective. The Last Show with David Cooper. Everyone says AI will make you so much more productive at work. That is if you haven't been laid off because of it. But what happens when that increased output really just turns into increased burnout? More is expected of you.
Are we upgrading our tools or are we downgrading our experience at the workplace with AI? We are joined by Brent Griffiths, a AI and tech reporter who has written about this recently at Business Insider. Brent, welcome to the show. Thanks for having me. So when you first heard this phrase, AI fatigue being thrown around by people in, you know, corporate environments, did it sound dramatic to you?
Chapter 2: What are the productivity gains expected from AI in the workplace?
Or did you immediately think like, oh, no, that's basically everyone right now?
It sounded a little dramatic. I feel like sometimes you get like those, you know, kind of like phrases and especially in kind of like workforce development, like quiet quitting. And you hear those, you're like, huh, that sounds interesting. Let me dig into that more. And I feel like this was a perfect example of that.
Chapter 3: How does increased productivity lead to burnout?
about these tools in the context of general work but also in the context of software engineering they're supposed to free up our time to make us do deeper thinking but what does that really mean in practice what does it mean for like me to have the tool do all the copywriting for me so i'm supposed to sit there and do what
That's a great question. And I feel like that's you've hit the nail on the head in terms of why software engineers are so frustrated. I've heard from some engineers who go running, they work out, some of them take naps. It's just kind of, you know, especially when you need this code and you can't really do something else in between, you're kind of stuck waiting.
And what are the sort of productivity expectations of workplaces now that engineers and employees have these tools to help them do their job?
I think it varies from place to place. But I talked to one engineer who wrote a viral essay about AI fatigue. And he talked about just how he feels like he's an assembly line because he's just he's plugging things into Claude or whatever coding agent he's using. And then he's reviewing the code and approving it instead of writing it himself. And
When, because he used to be able to write the code himself, he may be able to focus on one or two tasks a day. Now he's doing five or six, but it's not just reviewing the code that it's outputting, it's doing other tasks.
So he's being pulled in all these different directions and he's not really getting what he wanted out of the job, which was the ability to kind of think through hard problems and really tackle them kind of one by one.
That sort of sounds like to me like the crux of it. You're expected to produce more output, but your work kind of has like less meaning for you. And so you're just sitting there at your desk just as overworked as you might have been before, but kind of pulled in a thousand directions. Is that what people are saying that like their work is less meaningful with these tools? Absolutely.
Let's talk about like the review of the work.
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Chapter 4: What does AI fatigue mean for employees?
So when an engineer at a company produces like five different things instead of historically maybe one or two, who's doing the review of it? Are they expected to like fully read through it? Are their peers are expected to review it? Or are they just shipping things not really knowing what is in the code?
I think it's a combination. I think in a lot of cases, it's the engineer themselves who's putting that prompt into a coding agent and then getting that output. And then they're expected to go through and review it before they finish the pull requests.
Talk to me about this paradox that can arise where AI sort of like lowers the cost of doing work, but it kind of raises the cost of coordinating it all.
Exactly. And I think that's something that both the AI companies themselves and I think also the companies that are paying for these tools are really still kind of grappling with. And that, you know, like you said, AI was supposed to make people more productive and make things more efficient. But what you've essentially added in some cases is a kind of slower bureaucracy.
And also, you know, people still have to do what they were normally doing before as well. And we haven't even got to the other part, which is that, you know, these AI tools are not 100% reliable, right? And, you know, humans were not 100% reliable for either.
But, you know, for every time you have a great experience with a coding agent, there's a lot of other times where you're just constantly trying to plug in more prompts to get what you want, and you're not getting that result that you hoped for.
Now, is this all unique to like tech workers, software engineers, or does it sort of fan out to other disciplines that can use AI to be more productive as well?
I think it fans out to other disciplines. I think when you talk to software engineers, their fear is that a lot of AI companies focused on coding and programming to begin with for a couple of different reasons. And so now they're fearful that what they're experiencing is going to be what's in store for the lawyer or for someone on Wall Street or for even a journalist like me.
As AI begins to get smarter and become more efficient and can tackle kind of more detailed issues.
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