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[gentle music] Alex here. This episode is brought to you by our friends at Metricool. I'll be honest about my relationship with social media. I don't love using it personally.
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Unfortunately, social media is an absolute essential for work. Significant amount of Superpath's growth traces back to LinkedIn, but it's the single most distracting part of my week.
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I sit down to write, I open LinkedIn to schedule one post, and 40 minutes later I'm reading a thread about something that has nothing to do with Superpath or content marketing.
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The other thing that bugs me is that it never closes. There's always one more comment sitting there, one more thing to queue up before tomorrow morning.
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Metricool surveyed people who do this professionally, like me, and more than a half said they feel as overwhelmed as I do.
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Metricool wrangles the chaos of social media marketing with one streamlined calendar for all of your channels so you can schedule content, format posts, and interpret analytics all in one place instead of opening five different distracting apps.
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It tells me the best time to post based on my own account data rather than generic benchmarking. And the reporting sits right there, so I know what actually worked from last month.
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My favorite part is that there's one single inbox to manage all of your conversations across different channels. Over three and a half million professionals use Metricool daily.
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Start free or get 30 days of any premium plan with our Superpath code. The link and that code are in the show notes. Enjoy the episode. Alex here. Welcome to Content Briefly.
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Today, Rachel, Ruth, Chloe, and I talk about work slop, the AI mess that we have to deal with day to day from our coworkers and the world around us. What do we do when we come across it? How do we deal with it?
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With more companies establishing guidelines around how and when a coworker's allowed to use AI when they communicate with each other, are we finally leaving the messiest stage of this, or is there more to come?
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Hope you enjoy the episode. State of work slop. Anybody wanna kick us off?
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From my perspective, I've had several conversations lately with people that think we are post-peak work slop, that we are starting to push back on it, and the next chapter will be actually we wanna put some more humanness into what we're doing.
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And maybe these same executives that for the past year and a half were like, "Ooh, let's just AI everything," are going to start to, like, introduce some nuance into that.
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Either, like, getting, like, more gigs for that or I'm trying to hire for this balance of, like, somebody that will use AI smartly but not overuse AI. Who are you hearing that from? Um, startup folks mainly.
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Founders or, like, people hiring at earlier stage startups. Industry makes a big difference. Yeah. Right? A lot of industries that us and other folks in Superpath work with are very much still on the cutting edge of AI.
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So I think to say, like, we're past peak work slop might be true for people whose AI usage has already, like, been ahead of the curve, but when I walk around my small town, there's still, like, AI posters everywhere.
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I don't know that we've passed it all over the place, but I do think the pendulum is starting to swing. Let me rephrase that as not past AI slop.
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I think there's a lot more pushback to it now, and not in a way of like, haha, AI slop- I think that's true... but, like, it's kind of like the interest in, ooh, let's do everything with AI.
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I, I think AI slop will continue to rise, but I think the people that are trying to accomplish things with the AI slop marketing that they're doing are like, "Hey, maybe we need to not just push out a bunch of stuff."
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Yeah, I think the shine has worn off. Yes, that's a good way of putting it. Yeah, absolutely. How much time are you guys spending on socials? Outside of LinkedIn is what I mean. Because I spend a lot of time on threads.
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The way that I am approaching AI in my creative work is influenced a lot by what I read on my personal, on my personal socials [laughs].
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You know, there is a lot of hatred towards AI right now in everyday people, which is challenging and interesting to try to work through.
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How do you now use this technology in a way to not create work slop and ensure that that isn't the purpose of what you are trying to use these tools for, right?
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Because everything [laughs] online is, "I'm not gonna go to your restaurant if you're using AI to make your menu. Why are you using AI to take photos of your food?"
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W- Or, "If you're using AI to create your flyers, I would rather you take stock images than you put together something with ChatGPT."
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And it's so easy to tell now when something is an AI-generated email that you just copied and pasted from ChatGPT. There's emojis in it. Half of it is bolded. There's, "It's not X, it's Y" statements.
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There's, there's [laughs] a whole lot of that.
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And to your point, Rachel, of, like, the early adopters are past that, I think those people who are in that middle adoption curve are using these tools and are facing that backlash now of like, "No, don't use it.
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If you do... If you use it, you are not a good person and your work sucks."
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[laughs] Whereas a lot of us who use it early on are like, "Well, we know how to use it in a way that is actually gonna work for us, and let's do that strategically," right? How do we balance that?
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That is what I'm trying to figure out now, and I'm curious if you guys are seeing the same thing, if you've thought about that at all, or if that has found its way into your work slop thoughts.
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So I would say I was not an early adopter of AI.
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Like, I spent, like, a good chunk of time being like, "I hate everything about this," and realizing over time, like, sticking your head in the sand isn't gonna get you anywhere, right?
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I feel like now we've come to kind of like Google. We know that people are probably using it in some way, but I don't think it's like this black and white, like, we hate AI, we love AI.
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It's more like we know that you probably have some AI tool like Claude, Gemini, ChatGPT, whatever, open in your browser or on your desktop at some point in your day every single day. That's okay.
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I think that it's, like, the over-reliance on it that I still don't like. I edited something today, and I didn't open Claude once, and I was like, "Go me." And I don't like the fact that I have to celebrate that
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There's this push and pull between people that obviously have more of a creative mindset in marketing, right? But I will say I don't know if I'm seeing executives actually use it less.
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I actually think they're using it more.
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Where maybe people have varying comfort levels, and maybe where I'm starting to see the pendulum swing, is people being more comfortable calling it out and being like, "Did you use AI to do this?"
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Like, if I generate something and I mostly did, like, a shitty first draft with Claude for, like, an outline or something like that, I'll call it out. I'll be like, "This is part my brain and part Claude."
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Not everyone does that. I think I, I ran a poll on my LinkedIn to ask people if they, if they say anything or not, and it was pretty, like, evenly split. A couple things.
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First, to what Ruth said, I don't have a lot of social media accounts outside of LinkedIn, but I think we all know, like, social media is not nuanced.
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Yes, people online will be like, "Everyone who uses this thing is an evil person," but in real life, people tend to have much more nuanced takes of things.
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I do think a lot of the backlash is related to people starting to experience work slop in real life. Seeing AI posters at all of your favorite small business restaurants feels like work slop in real life.
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People feel like they're getting shorted or like somebody didn't care, or that there's something that place is hiding. There's some emotional reason why that feels bad to people.
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Everybody can have different reasons, but I think the question of, like, what's happening with work slop and why is there so much backlash against these certain uses of AI, I think there's some overlap there.
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To Chloe's point about the adoption curve and having some kind of AI tool open in your browser every day, I work part-time at a farm.
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I was chatting with another one of the girls who works in the flower fields with me, and she mentioned something about Claude, and another one of the farm workers who works there full time said, "Who's Claude?"
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And so I think, like, I just wanna say that to say even though you, Chloe, feel like, "Oh, I'm a really late adopter," compared to the general population- Yeah...
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you are still extremely ahead of the curve if you are thinking like, "Oh, everybody's using AI every day." And we're in such a bubble. Right. Given, like, the field that we're in. It's, it's a super insular bubble...
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given the conversations that we're having. And I think we forget that sometimes, that w- we're in this bubble, right? Um, I also saw this recently in my job search.
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Not every company that I was interviewing had the same level of AI adoption at their org, or was trying to have the same level of AI adoption.
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I remember I met with one company that was, like, very, very honest with me about like, "You know, this is kind of a legacy industry." It was like heavy machinery or something, but they were trying to transform.
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And the guy was like, "If you were the person that were to take this role, you would have some challenges in driving that transformation, because these are people who have been in these roles for like 20-plus years.
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They're used to doing things one way. They're used to these long processes. How do you tell them like, 'Oh, well, you can do that overnight?'"
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I think it's interesting 'cause obviously I work for a, a company that does workforce intelligence and, and workforce analytics, so we talk a lot about how AI and just how the workforce is changing in general.
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What I have realized, and this seems like a really obvious statement, but again, it goes back to us talking about us being in a bubble, is that the experience for AI is so different for everyone.
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There's positive emotions associated with it. There's negative emotions associated with it. There's this level of, like, excitement and, "Oh my God, the world is my oyster, and look at all these things I can do."
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But then I think there's a real fear, of course, still, that it is gonna displace people and their jobs, and the data's going every which way on that in terms of whether that's actually happening.
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So I'm like right in the thick of it, talking about these things and understanding more about workforce transformation, and particularly how AI is affecting it.
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That's where it's really important to just step outside of the bubble that we're in and think about [laughs] it's going to be somewhat forced upon us.
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And I think it's just up to the individual on how you perceive what you do with it being forced on you. I think that's a good point, and kind of goes back to Alex's question at the beginning.
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Narrowing in on this world of people who are using AI, and let's say are, like, AI fluent, what's the balance?
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How do you figure out how you're gonna use it, what you're gonna use it for, how you want your team to use it?
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I think the question I'm most interested in is where does that usage become work slop, and where does it stay being useful?
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Are you the person who gets to decide what that is, or is the person that you're giving it to the person who decides where that line is? I think there are a few obvious things.
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If you are just generating something and then you're passing it on, ew. [laughs] Like- Yeah, I agree I think we can have a big collective ew on that- Yes... on this call. Like, I think- Yes...
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we can all just go, "Ew, don't do that." I actually had, um, a data engineer share something today that said there's a new word that somebody has coined for that. So don't be that person. At least review it.
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And truthfully, Rachel, I think the person who is receiving it gets to decide, because they're the one who has to edit. They're the one who has to review.
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I think that's why it is so important to ensure that what you have guiding is actually approved by the entire team, and that everyone is on the same page with what is feeding it.
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So what I'm hearing from you, and I think this is a really good distinction to make, is there's a perception of trust when it comes to AI. Like, I don't think that's a surprise, right? Like, I...
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Would want to be known as the person who used AI to be more efficient at their job versus the person that's known for, oh, they just use AI for everything.
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That's a really important distinction because, like, if you're going to hand me something that I can tell you've just put a prompt in and handed me the first thing it spit back out, I'm not gonna trust you.
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I can do that. I can put in this prompt, and I can get the exact same thing, so, like, what value are you delivering to me?
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If you're not using that expertise in any way, to me, it's lazy, and it also dissolves my trust in you. Now, if you're honest about it, and you say, "I don't have time, so this is, like, I spent 10 minutes on this.
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I'm sorry. It's mostly AI. Let's iterate on it." Then I'm more likely to be like, "Okay, got it. Now I know what to expect."
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But if you're just gonna pass it off, and you expect me to think that you really did spend a hour, half hour, whatever it was supposed to be, to me, that's dishonest, and I'm gonna question everything you do.
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Some of the things I'm hearing are, like, effort, honesty, trust, expertise. I also wonder- Which are wildly human characteristics, let's just call out. [laughs] Right. Right.
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And I think, like, a lot of what frustrates us, I guess I'll just speak for myself, a lot of what frustrates me about work slop is that it feels like we have a human-to-human contract.
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If I ask you for your advice or I need something from you, and you give me something that feels dishonest or untrustworthy or uneffortful, it feels ew.
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It feels like you are breaking the contract that we set out of, like, we're gonna work on this project together.
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I also wonder how much of, like, I'm so busy I didn't have a half hour to do this, is caused by AI and work slop itself.
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The more that we use AI, the faster that we're expected to go, which means the more we're expected- Yes...
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to do, and then the more people have on their plates, the more they wanna pass off to AI, and then they wanna pass off my little task to AI, so then they give me work slop, and then I spend twice as long trying to wade through it, so then now I'm...
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You know what I mean? Like, and then it's just like this vicious cycle where we're supposed to be able to be more efficient and move faster with AI.
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I don't know if this is, like, a hot take or not, but I feel like it pretty much always slows me down.
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[laughs] Like, whether I'm receiving it from someone else or whether I'm using it myself, I think it can have many purposes and benefits, but I don't think that speed is actually one of them.
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This is why there is a lot to building out your actual AI foundation.
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My team has spent months building out the prompts and the skills and the knowledge base that we use in Claude, in Jira, in Google Docs that feeds everything that we use.
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If you are simply, "Hey, Claude, I need to create this. Here is a doc that I have. Go," you are not [laughs] gonna get something good, right?
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One thing that I think teams struggle with a lot of the time, it's something that I struggled with, is that you are trying to build it while also moving as fast as possible while being told, "Okay.
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Well, now that you can move as fast as possible, add more, more to your plate." Right. It's kinda like the strategy and tactics, right? Like, it's like you need to take a step back and be like, "Why are we doing this?
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What is actually our end goal? Like, what is this?" And no one wants to slow down to speed up, with, like, a super overused phrase, but, like, that's exactly what applies here.
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There's a lot of work I think that needs to be done. You know, we have guidelines. We have these things that we've loaded into Claude, and it's like, it's a start.
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Um, but in order to get it to where we really, really could use it to have something that's maybe 80% of the way there and only needs, like, a light human touch, it would take a lot more groundwork.
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And what I actually just had a conversation with my boss the other day, I was like, "I know that you want us to use AI more in our workflows, and I'm not disagreeing with you.
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But what I need then is protected time to, like, figure out what I actually need it to do rather than just solving for a random thing."
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Like, every single AI playbook is always like start with why, figure out what you actually want to accomplish. That's where you struggle, and you kinda go round and round and round.
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The times that AI has helped me save time has been when I have a really, really clear idea of what I'm trying to accomplish.
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I was able to use it to write a brief report in something that probably would've taken me, like, half a day, and, you know, I did it in, like, I don't know, hour and a half, two hour- Like, it, it was so much faster because I had a very clear-cut idea of what exactly I wanted.
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I think in that sense, AI can be really, really helpful, but I would never be like, "Okay, here's our brief. Write a blog for me," 'cause I want a human to do that. Right.
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My point about speed was, was more like what Ruth was saying. If we assume that we can use this thing to move fast and just jump right into it and 10X our speed, I don't know why I'm about to use this analogy.
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I don't know anything about cars. It's not like the kind of car that goes from zero to 60. You just step on the pedal and off you go, you know?
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[laughs] Like, this thing is like you have to, you have to soup up your little Honda Civic to make it make you go fast. [laughs] You know what I mean? You're right. I don't know why I chose that direction.
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You have to warm up the car, Rachel. [laughs] That works, too. That works, too. But I think that's more, like, the point that I was trying to make, was not that, like, AI can never save time.
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Obviously, lots of people are using it in lots of ways and saving time with it.
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But I think in order for that to really be possible, and more importantly, for it to, like, scale, actually do have to slow down, figure out what it works for and not, experiment, iterate, tinker around.
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These are all things that take time. People don't like it when things take time. [laughs]You know, and there are teams that are talking about, like, how long it takes, you know?
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Like, I was just listening to, um, a podcast episode where the CMO at Zapier was talking about, like, how did you get your giant marketing team to do something, to, like, actually go through this adoption cycle and start laying the foundation?
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And he was like, "We ran a two-week, a two-week hackathon, and yeah, all, all work was paused. Everyone had to build." You have to have time set a- apart to actually go execute.
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In my mind, I think I'm trying to use AI for the overall system versus for individual tasks, to your point, Chloe.
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To sorta go back to the idea peak AI slop, I'm now realizing, like, where that really comes from is from my people operations HR world that I'm still very adjacent to in LinkedIn.
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There've been a lot of tech companies lately that have basically rolled out these, like, giant policies recently around AI slop and, like, how it's used in the workplace.
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And as I, like, take a step back from that, what I think has happened, in a very broad sense, is that AI came onto the scene, and every company leader that's trying to, like, move faster, build things quicker, is like, "Great, let's do it.
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Let's, like, implement it right away. Let's throw it at everything." But it's kind of been a year-and-a-half-long experiment to see what sticks and is helpful and what isn't helpful.
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What, what I'm feeling is that we're finally getting to the stage where they're saying, "Great, we've run this very chaotic experiment for a year and a half, and now we're ready to lay down some rules about this.
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And it turns out we don't do better work when everybody is just giving AI answers to each other in Slack. We don't have a better content operation if we're just pushing out 100 blogs a month.
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That's not helping us achieve our goals. But we are finding efficiencies in X, Y, and Z places, and so we wanna continue to invest in AI in those spots."
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Another conversation I've had, I talked to somebody that was hiring for a, a content marketer in the past week or so. She was really struggling to find the right person.
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Now we've kind of gone into our little camps of I am super AI pilled, or I am very anti-AI.
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And she's like, "I really need somebody that sits in the middle, that has human judgment and knows what a good creative output looks like, and also is not, like..."
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She's like, "You know, you'll get on some of these conversations, and you've got somebody that can do that, but they're like, 'No. No, like, no AI at all. I will not change my process.
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A blog post is gonna take me a week and a half to write, and that's my process, and that's how I do it.'"
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And we do need the better efficiency that this enables, and we need somebody that believes that, but also somebody that's not just using Claude to do every single possible thing that's on their plate.
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That's why I just feel like we're entering a new stage, specifically the tech world that has been in this AI world for a year and a half, two years. I think it's all about setting expectations in that, though.
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Because, like, if I were looking at job descriptions, and I see things that are more around, like, AI-generated volume play, for example, I, I remember when I was job hunting, it told me a lot about the company the way that they approached AI, the job description, or in the initial interviews as well.
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Because again, there's what I would say, like, the good camp of AI.
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Like, "Hey, we're gonna give you the tools and resources to be able to explore how to use AI at your job, and we do expect you to use it, but we don't necessarily need you to use it for absolutely everything."
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And then there's the camp that's like, "Well, because you have access to AI, we now expect you to do 10 times the output and volume. And guess what? It's gonna be shitty."
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To me, it's like, just 'cause you can, should you? And that's what, like, AI can't answer. Do you guys know anyone in a role like that, though? That is in a role where they are purely using AI to generate volume? Yes.
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I, I know people that their bosses have expectations. See, and that's so interesting to me, because I don't. And anybody that I do, I- To clarify, not my boss.
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[laughs] Don't wanna go in this roundabout weird, like [laughs]... Hey, Dina, don't know if you listen to this, but that is not [laughs]
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See, I don't, and any team that I do run into who is like, "Yeah, we're trying to, like, scale our output from 10 to 100 a month," it's like, why are you doing that? No, I agree with you, but that is the expectation.
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Like, unless you're like- Yeah, there's definitely people out there... tweeting 100 times a month, then, like, okay. You can tweet 100 times a month. That makes sense. But blogs? That's... Oh, like, come on.
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We've seen the experiments. They're not great. Mm-hmm. But there are still people that think- That volume... if we just push out enough volume, something will work.
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Y'all, did you read this New York Times article a few weeks ago? There's this guy who writes a book a day using AI and just self-publishes on Amazon. Yes. It was fa- it was really fascinating. It was- Yes...
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he's written 500 books in the past two years. Most of them, nobody buys them. [laughs] Some will hit on a particular, like, topic area, where it's, like, 40 people buy them as, like, gifts for somebody else.
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And it was like he doesn't make much money off of it, but just, like, every single day, [laughs] he's just churning out a 400-page book off of AI. That's insane. I read that, too. It's the same premise...
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Uh, is this true? [laughs] I think it's true. [laughs] I think it's a similar premise to companies like, um, what's that clothing one? Shein? Is that- Yeah... is that what it is? Yeah.
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Where, like, that's cl- clothing slop, right? [laughs] Yeah. [laughs] Yeah. That's clothes slop. And- Yeah...
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on behalf of, like, the brand, the idea doesn't have to be good, because we're, we're making it at such a low cost that as long as enough people buy it, it's still profitable.
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And people who buy and wear Shein, I think, have the same idea. That, like, it doesn't matter if I only get one wear out of it, because it was only $5 or whatever it costs. It's fast fashion.
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Absolutely, like- A similar concept to some of these teams or individuals using AI in this way, feeling like it doesn't matter if this is a good or a bad idea.
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It's happening at such a low current cost to me personally- Mm-hmm... that as long as I can increase my quantity, I can still make some money. Like, I'm not advocating for this.
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I'm just saying I think this is the thought process behind it, and absolutely people are doing it. That's bad SEO. [laughs] Flood, well, flood the market and something will hit, like, that, yeah. Exactly.
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Throw enough darts and you'll hit the board eventually. And that looks different, like, if you're at an enterprise B2B company, but like, uh- Yeah...
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the more you get into B2C, like, it's just like that, you start to, like, can rationalize that, I think, a lot more in those spaces.
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If you're trying to run these big contracts and convince people of stuff, I, that looks different, I think. Yeah, definitely. Yeah.
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And that may be part of the reason, Alex, while you're starting to see a lot of these companies kind of hit their peak slop phase. I think it might take longer in the B2C realm for that to happen.
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But I think on B2B, there is less space to experiment and try a bunch of stuff. You have to, like, try stuff and figure out if it's working. If it's not working, you have to switch. Mm-hmm.
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The common theme that I'm hearing is that you just need to focus, streamline what you're actually trying to accomplish, whether that's, like, your marketing strategy or how you're going about your campaigns, or you're creating content or whatever.
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It's like, if you're trying to do all of the things, you're doing nothing. Pick one thing that you, like, really want AI to solve for you, and, like, focus on that.
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One or two channels, and focus on those instead of just being mediocre at literally everything. Because AI is so accessible and seemingly easy, everyone is assuming that eventually it can do everything.
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But just because it maybe can, should it? That's, like, the question that you have to, like, continually ask yourself. I think that's a good place to end it. Ruth, Rachel, Chloe, thanks for joining me.
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Good to be here, guys. Thanks for having me. Always fun. Woo. [outro music]
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[gentle music] Alex here. This episode is brought to you by our friends at Metricool. I'll be honest about my relationship with social media. I don't love using it personally.
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Unfortunately, social media is an absolute essential for work. Significant amount of Superpath's growth traces back to LinkedIn, but it's the single most distracting part of my week.
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I sit down to write, I open LinkedIn to schedule one post, and 40 minutes later I'm reading a thread about something that has nothing to do with Superpath or content marketing.
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The other thing that bugs me is that it never closes. There's always one more comment sitting there, one more thing to queue up before tomorrow morning.
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Metricool surveyed people who do this professionally, like me, and more than a half said they feel as overwhelmed as I do.
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Metricool wrangles the chaos of social media marketing with one streamlined calendar for all of your channels so you can schedule content, format posts, and interpret analytics all in one place instead of opening five different distracting apps.
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It tells me the best time to post based on my own account data rather than generic benchmarking. And the reporting sits right there, so I know what actually worked from last month.
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My favorite part is that there's one single inbox to manage all of your conversations across different channels. Over three and a half million professionals use Metricool daily.
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Start free or get 30 days of any premium plan with our Superpath code. The link and that code are in the show notes. Enjoy the episode. Alex here. Welcome to Content Briefly.
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Today, Rachel, Ruth, Chloe, and I talk about work slop, the AI mess that we have to deal with day to day from our coworkers and the world around us. What do we do when we come across it? How do we deal with it?
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With more companies establishing guidelines around how and when a coworker's allowed to use AI when they communicate with each other, are we finally leaving the messiest stage of this, or is there more to come?
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Hope you enjoy the episode. State of work slop. Anybody wanna kick us off?
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From my perspective, I've had several conversations lately with people that think we are post-peak work slop, that we are starting to push back on it, and the next chapter will be actually we wanna put some more humanness into what we're doing.
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And maybe these same executives that for the past year and a half were like, "Ooh, let's just AI everything," are going to start to, like, introduce some nuance into that.
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Either, like, getting, like, more gigs for that or I'm trying to hire for this balance of, like, somebody that will use AI smartly but not overuse AI. Who are you hearing that from? Um, startup folks mainly.
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Founders or, like, people hiring at earlier stage startups. Industry makes a big difference. Yeah. Right? A lot of industries that us and other folks in Superpath work with are very much still on the cutting edge of AI.
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So I think to say, like, we're past peak work slop might be true for people whose AI usage has already, like, been ahead of the curve, but when I walk around my small town, there's still, like, AI posters everywhere.
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I don't know that we've passed it all over the place, but I do think the pendulum is starting to swing. Let me rephrase that as not past AI slop.
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I think there's a lot more pushback to it now, and not in a way of like, haha, AI slop- I think that's true... but, like, it's kind of like the interest in, ooh, let's do everything with AI.
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I, I think AI slop will continue to rise, but I think the people that are trying to accomplish things with the AI slop marketing that they're doing are like, "Hey, maybe we need to not just push out a bunch of stuff."
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Yeah, I think the shine has worn off. Yes, that's a good way of putting it. Yeah, absolutely. How much time are you guys spending on socials? Outside of LinkedIn is what I mean. Because I spend a lot of time on threads.
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The way that I am approaching AI in my creative work is influenced a lot by what I read on my personal, on my personal socials [laughs].
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You know, there is a lot of hatred towards AI right now in everyday people, which is challenging and interesting to try to work through.
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How do you now use this technology in a way to not create work slop and ensure that that isn't the purpose of what you are trying to use these tools for, right?
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Because everything [laughs] online is, "I'm not gonna go to your restaurant if you're using AI to make your menu. Why are you using AI to take photos of your food?"
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W- Or, "If you're using AI to create your flyers, I would rather you take stock images than you put together something with ChatGPT."
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And it's so easy to tell now when something is an AI-generated email that you just copied and pasted from ChatGPT. There's emojis in it. Half of it is bolded. There's, "It's not X, it's Y" statements.
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There's, there's [laughs] a whole lot of that.
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And to your point, Rachel, of, like, the early adopters are past that, I think those people who are in that middle adoption curve are using these tools and are facing that backlash now of like, "No, don't use it.
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If you do... If you use it, you are not a good person and your work sucks."
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[laughs] Whereas a lot of us who use it early on are like, "Well, we know how to use it in a way that is actually gonna work for us, and let's do that strategically," right? How do we balance that?
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That is what I'm trying to figure out now, and I'm curious if you guys are seeing the same thing, if you've thought about that at all, or if that has found its way into your work slop thoughts.
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So I would say I was not an early adopter of AI.
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Like, I spent, like, a good chunk of time being like, "I hate everything about this," and realizing over time, like, sticking your head in the sand isn't gonna get you anywhere, right?
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I feel like now we've come to kind of like Google. We know that people are probably using it in some way, but I don't think it's like this black and white, like, we hate AI, we love AI.
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It's more like we know that you probably have some AI tool like Claude, Gemini, ChatGPT, whatever, open in your browser or on your desktop at some point in your day every single day. That's okay.
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I think that it's, like, the over-reliance on it that I still don't like. I edited something today, and I didn't open Claude once, and I was like, "Go me." And I don't like the fact that I have to celebrate that
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There's this push and pull between people that obviously have more of a creative mindset in marketing, right? But I will say I don't know if I'm seeing executives actually use it less.
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I actually think they're using it more.
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Where maybe people have varying comfort levels, and maybe where I'm starting to see the pendulum swing, is people being more comfortable calling it out and being like, "Did you use AI to do this?"
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Like, if I generate something and I mostly did, like, a shitty first draft with Claude for, like, an outline or something like that, I'll call it out. I'll be like, "This is part my brain and part Claude."
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Not everyone does that. I think I, I ran a poll on my LinkedIn to ask people if they, if they say anything or not, and it was pretty, like, evenly split. A couple things.
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First, to what Ruth said, I don't have a lot of social media accounts outside of LinkedIn, but I think we all know, like, social media is not nuanced.
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Yes, people online will be like, "Everyone who uses this thing is an evil person," but in real life, people tend to have much more nuanced takes of things.
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I do think a lot of the backlash is related to people starting to experience work slop in real life. Seeing AI posters at all of your favorite small business restaurants feels like work slop in real life.
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People feel like they're getting shorted or like somebody didn't care, or that there's something that place is hiding. There's some emotional reason why that feels bad to people.
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Everybody can have different reasons, but I think the question of, like, what's happening with work slop and why is there so much backlash against these certain uses of AI, I think there's some overlap there.
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To Chloe's point about the adoption curve and having some kind of AI tool open in your browser every day, I work part-time at a farm.
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I was chatting with another one of the girls who works in the flower fields with me, and she mentioned something about Claude, and another one of the farm workers who works there full time said, "Who's Claude?"
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And so I think, like, I just wanna say that to say even though you, Chloe, feel like, "Oh, I'm a really late adopter," compared to the general population- Yeah...
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you are still extremely ahead of the curve if you are thinking like, "Oh, everybody's using AI every day." And we're in such a bubble. Right. Given, like, the field that we're in. It's, it's a super insular bubble...
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given the conversations that we're having. And I think we forget that sometimes, that w- we're in this bubble, right? Um, I also saw this recently in my job search.
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Not every company that I was interviewing had the same level of AI adoption at their org, or was trying to have the same level of AI adoption.
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I remember I met with one company that was, like, very, very honest with me about like, "You know, this is kind of a legacy industry." It was like heavy machinery or something, but they were trying to transform.
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And the guy was like, "If you were the person that were to take this role, you would have some challenges in driving that transformation, because these are people who have been in these roles for like 20-plus years.
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They're used to doing things one way. They're used to these long processes. How do you tell them like, 'Oh, well, you can do that overnight?'"
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I think it's interesting 'cause obviously I work for a, a company that does workforce intelligence and, and workforce analytics, so we talk a lot about how AI and just how the workforce is changing in general.
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What I have realized, and this seems like a really obvious statement, but again, it goes back to us talking about us being in a bubble, is that the experience for AI is so different for everyone.
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There's positive emotions associated with it. There's negative emotions associated with it. There's this level of, like, excitement and, "Oh my God, the world is my oyster, and look at all these things I can do."
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But then I think there's a real fear, of course, still, that it is gonna displace people and their jobs, and the data's going every which way on that in terms of whether that's actually happening.
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So I'm like right in the thick of it, talking about these things and understanding more about workforce transformation, and particularly how AI is affecting it.
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That's where it's really important to just step outside of the bubble that we're in and think about [laughs] it's going to be somewhat forced upon us.
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And I think it's just up to the individual on how you perceive what you do with it being forced on you. I think that's a good point, and kind of goes back to Alex's question at the beginning.
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Narrowing in on this world of people who are using AI, and let's say are, like, AI fluent, what's the balance?
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How do you figure out how you're gonna use it, what you're gonna use it for, how you want your team to use it?
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I think the question I'm most interested in is where does that usage become work slop, and where does it stay being useful?
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Are you the person who gets to decide what that is, or is the person that you're giving it to the person who decides where that line is? I think there are a few obvious things.
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If you are just generating something and then you're passing it on, ew. [laughs] Like- Yeah, I agree I think we can have a big collective ew on that- Yes... on this call. Like, I think- Yes...
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we can all just go, "Ew, don't do that." I actually had, um, a data engineer share something today that said there's a new word that somebody has coined for that. So don't be that person. At least review it.
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And truthfully, Rachel, I think the person who is receiving it gets to decide, because they're the one who has to edit. They're the one who has to review.
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I think that's why it is so important to ensure that what you have guiding is actually approved by the entire team, and that everyone is on the same page with what is feeding it.
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So what I'm hearing from you, and I think this is a really good distinction to make, is there's a perception of trust when it comes to AI. Like, I don't think that's a surprise, right? Like, I...
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Would want to be known as the person who used AI to be more efficient at their job versus the person that's known for, oh, they just use AI for everything.
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That's a really important distinction because, like, if you're going to hand me something that I can tell you've just put a prompt in and handed me the first thing it spit back out, I'm not gonna trust you.
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I can do that. I can put in this prompt, and I can get the exact same thing, so, like, what value are you delivering to me?
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If you're not using that expertise in any way, to me, it's lazy, and it also dissolves my trust in you. Now, if you're honest about it, and you say, "I don't have time, so this is, like, I spent 10 minutes on this.
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I'm sorry. It's mostly AI. Let's iterate on it." Then I'm more likely to be like, "Okay, got it. Now I know what to expect."
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But if you're just gonna pass it off, and you expect me to think that you really did spend a hour, half hour, whatever it was supposed to be, to me, that's dishonest, and I'm gonna question everything you do.
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Some of the things I'm hearing are, like, effort, honesty, trust, expertise. I also wonder- Which are wildly human characteristics, let's just call out. [laughs] Right. Right.
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And I think, like, a lot of what frustrates us, I guess I'll just speak for myself, a lot of what frustrates me about work slop is that it feels like we have a human-to-human contract.
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If I ask you for your advice or I need something from you, and you give me something that feels dishonest or untrustworthy or uneffortful, it feels ew.
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It feels like you are breaking the contract that we set out of, like, we're gonna work on this project together.
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I also wonder how much of, like, I'm so busy I didn't have a half hour to do this, is caused by AI and work slop itself.
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The more that we use AI, the faster that we're expected to go, which means the more we're expected- Yes...
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to do, and then the more people have on their plates, the more they wanna pass off to AI, and then they wanna pass off my little task to AI, so then they give me work slop, and then I spend twice as long trying to wade through it, so then now I'm...
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You know what I mean? Like, and then it's just like this vicious cycle where we're supposed to be able to be more efficient and move faster with AI.
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I don't know if this is, like, a hot take or not, but I feel like it pretty much always slows me down.
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[laughs] Like, whether I'm receiving it from someone else or whether I'm using it myself, I think it can have many purposes and benefits, but I don't think that speed is actually one of them.
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This is why there is a lot to building out your actual AI foundation.
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My team has spent months building out the prompts and the skills and the knowledge base that we use in Claude, in Jira, in Google Docs that feeds everything that we use.
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If you are simply, "Hey, Claude, I need to create this. Here is a doc that I have. Go," you are not [laughs] gonna get something good, right?
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One thing that I think teams struggle with a lot of the time, it's something that I struggled with, is that you are trying to build it while also moving as fast as possible while being told, "Okay.
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Well, now that you can move as fast as possible, add more, more to your plate." Right. It's kinda like the strategy and tactics, right? Like, it's like you need to take a step back and be like, "Why are we doing this?
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What is actually our end goal? Like, what is this?" And no one wants to slow down to speed up, with, like, a super overused phrase, but, like, that's exactly what applies here.
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There's a lot of work I think that needs to be done. You know, we have guidelines. We have these things that we've loaded into Claude, and it's like, it's a start.
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Um, but in order to get it to where we really, really could use it to have something that's maybe 80% of the way there and only needs, like, a light human touch, it would take a lot more groundwork.
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And what I actually just had a conversation with my boss the other day, I was like, "I know that you want us to use AI more in our workflows, and I'm not disagreeing with you.
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But what I need then is protected time to, like, figure out what I actually need it to do rather than just solving for a random thing."
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Like, every single AI playbook is always like start with why, figure out what you actually want to accomplish. That's where you struggle, and you kinda go round and round and round.
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The times that AI has helped me save time has been when I have a really, really clear idea of what I'm trying to accomplish.
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I was able to use it to write a brief report in something that probably would've taken me, like, half a day, and, you know, I did it in, like, I don't know, hour and a half, two hour- Like, it, it was so much faster because I had a very clear-cut idea of what exactly I wanted.
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I think in that sense, AI can be really, really helpful, but I would never be like, "Okay, here's our brief. Write a blog for me," 'cause I want a human to do that. Right.
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My point about speed was, was more like what Ruth was saying. If we assume that we can use this thing to move fast and just jump right into it and 10X our speed, I don't know why I'm about to use this analogy.
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I don't know anything about cars. It's not like the kind of car that goes from zero to 60. You just step on the pedal and off you go, you know?
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[laughs] Like, this thing is like you have to, you have to soup up your little Honda Civic to make it make you go fast. [laughs] You know what I mean? You're right. I don't know why I chose that direction.
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You have to warm up the car, Rachel. [laughs] That works, too. That works, too. But I think that's more, like, the point that I was trying to make, was not that, like, AI can never save time.
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Obviously, lots of people are using it in lots of ways and saving time with it.
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But I think in order for that to really be possible, and more importantly, for it to, like, scale, actually do have to slow down, figure out what it works for and not, experiment, iterate, tinker around.
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These are all things that take time. People don't like it when things take time. [laughs]You know, and there are teams that are talking about, like, how long it takes, you know?
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Like, I was just listening to, um, a podcast episode where the CMO at Zapier was talking about, like, how did you get your giant marketing team to do something, to, like, actually go through this adoption cycle and start laying the foundation?
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And he was like, "We ran a two-week, a two-week hackathon, and yeah, all, all work was paused. Everyone had to build." You have to have time set a- apart to actually go execute.
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In my mind, I think I'm trying to use AI for the overall system versus for individual tasks, to your point, Chloe.
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To sorta go back to the idea peak AI slop, I'm now realizing, like, where that really comes from is from my people operations HR world that I'm still very adjacent to in LinkedIn.
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There've been a lot of tech companies lately that have basically rolled out these, like, giant policies recently around AI slop and, like, how it's used in the workplace.
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And as I, like, take a step back from that, what I think has happened, in a very broad sense, is that AI came onto the scene, and every company leader that's trying to, like, move faster, build things quicker, is like, "Great, let's do it.
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Let's, like, implement it right away. Let's throw it at everything." But it's kind of been a year-and-a-half-long experiment to see what sticks and is helpful and what isn't helpful.
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What, what I'm feeling is that we're finally getting to the stage where they're saying, "Great, we've run this very chaotic experiment for a year and a half, and now we're ready to lay down some rules about this.
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And it turns out we don't do better work when everybody is just giving AI answers to each other in Slack. We don't have a better content operation if we're just pushing out 100 blogs a month.
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That's not helping us achieve our goals. But we are finding efficiencies in X, Y, and Z places, and so we wanna continue to invest in AI in those spots."
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Another conversation I've had, I talked to somebody that was hiring for a, a content marketer in the past week or so. She was really struggling to find the right person.
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Now we've kind of gone into our little camps of I am super AI pilled, or I am very anti-AI.
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And she's like, "I really need somebody that sits in the middle, that has human judgment and knows what a good creative output looks like, and also is not, like..."
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She's like, "You know, you'll get on some of these conversations, and you've got somebody that can do that, but they're like, 'No. No, like, no AI at all. I will not change my process.
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A blog post is gonna take me a week and a half to write, and that's my process, and that's how I do it.'"
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And we do need the better efficiency that this enables, and we need somebody that believes that, but also somebody that's not just using Claude to do every single possible thing that's on their plate.
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That's why I just feel like we're entering a new stage, specifically the tech world that has been in this AI world for a year and a half, two years. I think it's all about setting expectations in that, though.
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Because, like, if I were looking at job descriptions, and I see things that are more around, like, AI-generated volume play, for example, I, I remember when I was job hunting, it told me a lot about the company the way that they approached AI, the job description, or in the initial interviews as well.
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Because again, there's what I would say, like, the good camp of AI.
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Like, "Hey, we're gonna give you the tools and resources to be able to explore how to use AI at your job, and we do expect you to use it, but we don't necessarily need you to use it for absolutely everything."
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And then there's the camp that's like, "Well, because you have access to AI, we now expect you to do 10 times the output and volume. And guess what? It's gonna be shitty."
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To me, it's like, just 'cause you can, should you? And that's what, like, AI can't answer. Do you guys know anyone in a role like that, though? That is in a role where they are purely using AI to generate volume? Yes.
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I, I know people that their bosses have expectations. See, and that's so interesting to me, because I don't. And anybody that I do, I- To clarify, not my boss.
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[laughs] Don't wanna go in this roundabout weird, like [laughs]... Hey, Dina, don't know if you listen to this, but that is not [laughs]
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See, I don't, and any team that I do run into who is like, "Yeah, we're trying to, like, scale our output from 10 to 100 a month," it's like, why are you doing that? No, I agree with you, but that is the expectation.
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Like, unless you're like- Yeah, there's definitely people out there... tweeting 100 times a month, then, like, okay. You can tweet 100 times a month. That makes sense. But blogs? That's... Oh, like, come on.
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We've seen the experiments. They're not great. Mm-hmm. But there are still people that think- That volume... if we just push out enough volume, something will work.
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Y'all, did you read this New York Times article a few weeks ago? There's this guy who writes a book a day using AI and just self-publishes on Amazon. Yes. It was fa- it was really fascinating. It was- Yes...
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he's written 500 books in the past two years. Most of them, nobody buys them. [laughs] Some will hit on a particular, like, topic area, where it's, like, 40 people buy them as, like, gifts for somebody else.
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And it was like he doesn't make much money off of it, but just, like, every single day, [laughs] he's just churning out a 400-page book off of AI. That's insane. I read that, too. It's the same premise...
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Uh, is this true? [laughs] I think it's true. [laughs] I think it's a similar premise to companies like, um, what's that clothing one? Shein? Is that- Yeah... is that what it is? Yeah.
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Where, like, that's cl- clothing slop, right? [laughs] Yeah. [laughs] Yeah. That's clothes slop. And- Yeah...
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on behalf of, like, the brand, the idea doesn't have to be good, because we're, we're making it at such a low cost that as long as enough people buy it, it's still profitable.
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And people who buy and wear Shein, I think, have the same idea. That, like, it doesn't matter if I only get one wear out of it, because it was only $5 or whatever it costs. It's fast fashion.
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Absolutely, like- A similar concept to some of these teams or individuals using AI in this way, feeling like it doesn't matter if this is a good or a bad idea.
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It's happening at such a low current cost to me personally- Mm-hmm... that as long as I can increase my quantity, I can still make some money. Like, I'm not advocating for this.
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I'm just saying I think this is the thought process behind it, and absolutely people are doing it. That's bad SEO. [laughs] Flood, well, flood the market and something will hit, like, that, yeah. Exactly.
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Throw enough darts and you'll hit the board eventually. And that looks different, like, if you're at an enterprise B2B company, but like, uh- Yeah...
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the more you get into B2C, like, it's just like that, you start to, like, can rationalize that, I think, a lot more in those spaces.
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If you're trying to run these big contracts and convince people of stuff, I, that looks different, I think. Yeah, definitely. Yeah.
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And that may be part of the reason, Alex, while you're starting to see a lot of these companies kind of hit their peak slop phase. I think it might take longer in the B2C realm for that to happen.
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But I think on B2B, there is less space to experiment and try a bunch of stuff. You have to, like, try stuff and figure out if it's working. If it's not working, you have to switch. Mm-hmm.
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The common theme that I'm hearing is that you just need to focus, streamline what you're actually trying to accomplish, whether that's, like, your marketing strategy or how you're going about your campaigns, or you're creating content or whatever.
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It's like, if you're trying to do all of the things, you're doing nothing. Pick one thing that you, like, really want AI to solve for you, and, like, focus on that.
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One or two channels, and focus on those instead of just being mediocre at literally everything. Because AI is so accessible and seemingly easy, everyone is assuming that eventually it can do everything.
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But just because it maybe can, should it? That's, like, the question that you have to, like, continually ask yourself. I think that's a good place to end it. Ruth, Rachel, Chloe, thanks for joining me.
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Good to be here, guys. Thanks for having me. Always fun. Woo. [outro music]
