Is AI Going to Turn Us All Into Middle Managers?

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How is AI changing the way we work? This week on Galaxy Brain, Charlie Warzel is joined by Johnathan and Melissa Nightingale, two experts in management and leadership training. They discuss how chatbots and AI agents are winding their way through the workforce, offering a firsthand view of how companies are (and aren’t) adopting AI tools. The conversation covers the gap between AI hype and what’s actually happening in offices. It also touches on how overreliance on AI tools may be making bosses worse at their jobs, and how work may be one of the last bastions of sustained social connection in a period of cultural alienation and isolation.

The following is a transcript of the episode:

Johnathan Nightingale: It turns out that humans really care about doing work they believe in, with people they care about. And when you hollow those things out, people have these emotional responses to it that I don’t see predicted by the marketing materials from the AI companies.

[Music]

Charlie Warzel: I’m Charlie Warzel, and this is Galaxy Brain: a show where today we are going to talk about work. Trying to talk about jobs right now—how we work, what that work means, what the future of white-collar work looks like—it is just extremely difficult.

We all seem to be situated in this very confusing moment, one that I think is captured very well by my Atlantic colleague Josh Tyrangiel’s story. It ran with this rather ominous headline: “America Isn’t Ready for What AI Will Do to Jobs.” The piece is great, and you should totally seek it out. But the illustration of the piece I found quite apt.

It’s of this man; he’s in a tree. His eyes are two dollar signs, and he’s smiling while holding a chainsaw and cutting into the branch that’s supporting his own weight. This in many ways is the vibe of 2026. This feeling that this certain subset of people motivated by profit and efficiency are conducting an experiment that, if it succeeds, is not gonna just rewire the economy forever but change the very nature and essence of labor.

For the last few years, since the arrival of chatbots, the AI conversation around work has been some version of this. The tools are useful in automating busywork and drudgery. They’re getting better.

And so what does that mean for jobs? Well, AI executives have been issuing dire warnings. In 2025, for example, Dario Amide—the CEO of the AI company Anthropic—told Axios that AI could drive unemployment up 10 to 20 percent in the next one to five years and wipe out half of all entry-level white-collar jobs.

Meanwhile, those who are running companies seem quite eager to unleash this technology on knowledge work—labor force be damned. They’re driven by profit incentives and a good amount of FOMO. AI is the future. Get on board or be left behind. What’s your AI strategy? In some cases, the fastest way to show results is to simply reduce head count.

Workers, especially young workers, are concerned. According to the Federal Reserve Bank of New York, the unemployment rate for college graduates ages 22 to 27 ballooned to 5.6 percent at the end of last year. And as The New York Times notes: “For those who are employed, more than 40 percent held jobs that do not typically require college degrees, the highest level since 2020.”

You can feel the weirdness in the economy right now. This fear of a kind of job-market stagnation, but no exact sense of what is happening on the ground. How much of all of this is actually AI driven? Simply put, there are huge fears here that AI is not only changing the way we might do our jobs, but it might be changing how we get them, whether we can keep them. AI executives are out here arguing that most of us, no matter the job, are destined to become middle managers for a host of AI agents. And you can take that with a grain of salt as just another tech CEO prognostication. But if there’s any truth to it, it would represent a massive change. And the concerns go well beyond the economy into something much more existential. What does it mean to be a human in a world that all of a sudden doesn’t value human labor in the same way?

So are we all destined to become middle managers? Is AI really ripping through the workforce? What is the value of work in this strange economy? And how can people survive—maintain dignity, human connection, all of that—in a world where decision makers driven by dollar signs are pruning the trees for every possible efficiency? Even if we’re all just sitting on the branches?

Johnathan and Melissa Nightingale are here to help me answer some of these thorny questions. They’re the founders of Raw Signal, a leadership and management training firm. Johnathan and Melissa have worked with thousands of executives and managers and companies across tech and other industries, and they’re keen observers of the ways that modern white-collar work and workplace communication is broken. But they also offer this clear vision of how work can stay human and humane. They join me now to talk it all through.

[Music]

Warzel: Melissa and Johnathan, welcome to Galaxy Brain.

Johnathan Nightingale: Thank you.

Melissa Nightingale: Thanks, Charlie.

Johnathan Nightingale: It’s lovely to be here.

Warzel: So it is a weird time in the economy, especially in America. We’re in this low-hire, low-fire labor market. There’s this very amorphous and pressing fear right now about artificial intelligence taking or threatening jobs, especially entry-level jobs. And the labor market just looks increasingly grim and feels increasingly grim to younger workers. The vibes—they’re off, they’re not good.

I wanted to start just by asking you all: You’re talking to businesses, to people. You’re on the ground. What are people telling you about the vibes right now? Report on the vibes for me.

Melissa Nightingale: I love “Report on the vibes.”

Johnathan Nightingale: “The vibes” is such a great place to start. Because I don’t know if you remember, but it wasn’t so many years ago that companies were appointing “chief vibes officers.”

Melissa Nightingale: Do you remember this? Like, in 2022?

Warzel: I don’t really, no.

Melissa Nightingale: Okay; there’s a very weird future-of-work moment where everybody was, like, a future-of-work thought leader in 2022. And The New York Times reported they had a big story about chief vibes officers being like…

Johnathan Nightingale: The new jobs of the new economy.

Warzel: Man, I missed out on that. I would love to be chief vibes officer.

Melissa Nightingale: But that was the new hot title.

Johnathan Nightingale: Because, like, in 2022, like everybody was fighting. I think junior engineers were getting, you know, 100, 200, 300,000-dollar offer packages because everybody was starved for this tech talent. And that was the story of the moment—“Wow, how much worker empowerment there is.”

Melissa Nightingale: And so, we’re not trying to make the vibe sad. But it is worth starting with: Where were the vibes as we head into … like, where are the vibes now? So 2022: still relatively hot labor market; still a lot of competition for talent. Particularly junior talent; particularly junior engineering talent.

Johnathan Nightingale: And you could tell that senior leaders were pissed off about them. It was too expensive. These people were too entitled, right? Like, “chief vibes officer” makes good buzz. But you could tell in early 2022 that this was about to get some pushback.

Melissa Nightingale: Remember, this was the earliest version of return-to-office mandates. People saying: “We went home. We did amazing work at home. Why do we have to go back? And also, like, if you make me go back, I have another $300,000 job offer lined up tomorrow.”

Johnathan Nightingale: Just walk across the street. And so, it’s funny because people talk about AI and all the layoffs. And there’s been, you know, half a million layoffs in the last several years, and technology workers and stuff like that. Those layoffs started before the first ChatGPT release.

Melissa Nightingale: What it did was reset the market, right? It recalibrated. Like, you had folks who had that sort of early engineering role. And they got a little bit more skittish about, Should I leave to go across the street, or should I stay put? Should I feel grateful that I have a job, that I have this opportunity? And you started to see people feeling a little bit more nervous, and a little bit more uncomfortable around the market overall.

Johnathan Nightingale: These days, AI has sucked all the oxygen out of the room. And people are like: “That’s all driven by AI.” I’m like: no. First of all, November ChatGPT couldn’t count how many Rs there were in strawberry. That’s not a reason to turn your whole business upside down. But also, the layoffs happened six months before that too. It’s really been part of a pattern of executives in some organizations reasserting power and making sure that, especially, junior workers lose that sense of entitlement. I think vibes-wise, that’s happened. They succeeded in that.

Warzel: It was such an interesting moment. I wrote back in—I think it was 2021, but it might’ve been 2022—in that time period of a hot labor market. Also of, as you say, some real worker empowerment. I remember writing this piece that was like: “Do workers, do people even want a career?” Right? Like, do the young, Gen Z people coming up, do they even want a career? They’re questioning the idea of the standard thing, because there’s just so many different options. And maybe I don’t want to work the way that my parents worked. And to compare that feeling to now, where it’s like “Could I even get in the door to have a career, or am I going to have to figure out something else completely different?” I think that that’s extremely stark in terms of that shift. What are people telling you on the ground now in terms of this moment? Obviously there is that sense of precarity with workers. But in terms of that force, of generative AI, how are people feeling about it?

Melissa Nightingale: Johnathan and I both come from tech, right? We’ve both been working in tech since the first dot-com boom, all the way on through. And we work with a lot of organizations with tech leaders. And what we’re hearing from folks is—on the one hand, you sign up for tech as your industry and as your career, you like working on the cool new stuff, right? Like, we are an industry that loves our toys. We love innovation. We love sort of taking things out and experimenting. Sometimes they last; sometimes they don’t last. But as an industry, if that doesn’t get you lit up, you’ve picked the wrong job.

But what we’re hearing from a lot of folks is that the day-to-day of “We’re playing with these tools” is no longer lining up to “What are we supposed to be doing here?” And that playing with the tools has become sort of an end into itself. And a lot of folks are finding: “We’re using them, but I don’t know—what are we running toward?”

Warzel: Do you get the sense that this is like, if we’re going down the chain: This is executives high up on top, see a thing. They’re reading a lot about it; there’s a lot of hype. They feel, Okay, more than anything, I have to make sure that we do not get left behind here. And then the sort of middle-manager layer is feeling that it’s forced on them. Or is there sort of, broadly speaking, a lot of enthusiasm—but there’s just not enough time to figure it out?

Melissa Nightingale: All of the above. Like, we met a lady who’s a really skilled executive, and she was working in an organization where she’s like: “I came in as a fixer, right? My whole job was fixer. And I was really excited about it. Like, the opportunity was cool. Came in, doing the work. And starting to see the impact of that work, right?” And she’s like, “And then my CEO got really excited about GPT, and I started sending things that were strategic plans for my division, for my department. And what started coming back from my CEO—who I report directly into—wasn’t from him. It was clear he hadn’t read any of the plans that I was putting forward. He just pushed them through and said, Generate an email in response to this.” And she’s like, “I went from being so excited about the turnaround potential for this business, for this organization, and for my department and team, to feeling really sad. Like fundamentally—just having a very hard time figuring out, What am I doing if I’m putting in all this effort?”

Johnathan Nightingale: When you look at a story like that—that’s a management failure. It can take one of a couple flavors. One thing you can say is, “That person’s work is now useless because GPT replaces it well enough. And so that person should have just been given a firm handshake and a goodbye package and sent out the door.” Or you can say “GPT can’t replace human ingenuity at the senior levels.” And so there’s a real dereliction there, because you had a motivated, engaged senior employee, and you burnt them. In either case, that’s a management failure. A thing that’s coming up a fair bit is that people look at what code generation can do in LLMs today. And they sort of do the “well naturally”: Well, naturally, in time, it will write good poems. Well, naturally, in time, it will be your accountant. And well, naturally, in time, it will manage as well or better than most people do. It’s just this leap, this linear leap, that is not borne out by what we’re seeing on the ground today.

Warzel: Do you feel like that’s a broader trend of, especially on the executive layer—and I’m not trying to paint people as caricatures here—but this idea that, especially with these higher, more like “vision strategy” jobs, where there is a lot of busywork involved in that sense of communication. That, you know, what I’ve heard is that AI is a perfect CEO, right? Like, it could be—it’s just sort of broad, broad pronouncements—being able to speak with maybe more confidence than is earned or deserved, right?

Johnathan Nightingale: Incredible executive presence.

Warzel: Great presence in that sense. And so, naturally, people higher up on the end of the management chain might be enamored with it or the ability of it. Do you feel like CEOs are overly AI-pilled right now?

Johnathan Nightingale: I think they’re a vulnerable group. I think one of the challenges with being a CEO is that even an incredibly effective CEO shouldn’t know more about every function in their business than the people working those functions do. Right? If you’re an expert engineer and you become a CEO, you might know a lot about engineering.

Melissa Nightingale: But over time, you’ll actually know less than the people who are typing on keyboards all day.

Johnathan Nightingale: And your head of sales should know more about sales than you do. Your head of marketing should know more about marketing than you do. Right? Like, that part of the job of building a senior team is to make sure those people are, one, lighting you on fire with great ideas, and two, are credible leaders for their own functions in a way that you couldn’t be. Because a person can’t know everything about everything. And so, it’s tempting from that seat to flatten a lot of that work, and to say “If an AI can do that work 80 percent as well, maybe I have to spend some more compute over there in order to get the result I want. But, like, do I even need a marketing department? Do I even need an engineering department? Do I even need a finance department?” They’re vulnerable to it if they don’t hold on to a sort of core “go touch grass” reality. Which is that it takes a long time to learn some things, and human judgment is valuable.

Warzel: Where do you all think we are in terms of adoption? Because again, for someone on the outside, who’s not speaking to managers and the rank-and-file types of employees at all times, it’s hard to get a good sense.

But how much have these tools already changed what is happening day in, day out? Versus how much of it is that feeling of like, I need to be doing this. This is something that we need to have? There is the, you know, the FOMO element. Where do you see the balance there?

Johnathan Nightingale: Certainly among the groups that we work with, people in engineering roles have been the most curious about it, and in some cases the most compelled to engage with it. You definitely have people who are very credulous—“We’re playing with it a lot”—who feel like they’re getting super productive about it. We’re starting to see studies about how those people are burning themselves out. Right? Those people are really struggling, because they’re orchestrating so many bots that they never want to close their laptop. Because they’re getting this dopamine hit from productivity. They’re not necessarily deepening their skills; they’re just doing a bunch of stuff. But like, there you see a ton of adoption.

Melissa Nightingale: We’re starting to see the fingerprints of AI-adoption mandates in context where it makes no damn sense. So like, prompt saying, “We have a client organization that was building technology to respond to bots infiltrating contact forms on websites.” Because so many people were having their agent basically go: “Reach out to this organization; we’re trying to get this work done. Can you go figure out a quote for this thing? Like, go write them with a description of what we’re trying to get done; have it come back.” But the cycle times are considerably longer, in part because the context that you can anticipate a human responding to it needing just isn’t there. And so you end up with, like—it’s meant to save a step, but it causes three more. And we’ve all had the experience of somebody like a junior person sending a shitty email and being like, Fuck, I gotta go unwind that. Right? Like, I gotta go unwind that you sent an email. And, it makes no damn sense. And now I’ve got 30 people in the organization going on, running and chasing a thing.

Johnathan Nightingale: Or “You sent it to a client, and now I gotta go apologize for that.”

Melissa Nightingale: Right. But imagine that multiplied across many workforces right now. Where you’ve got a lot of communication and requests flowing that, like, just missed an important key step before they went out the door. And so there’s a bunch of weird context and cleanup that’s taking longer than the original initial task would have taken to just do the damn thing.

Johnathan Nightingale: And there’s this rigidity forming, too, which is worth fighting against. Which is that you’ll have people farming everything out to GPT—even really obvious ways, right? You get emails from a colleague, and you’re like, “This is not what you sound like. This is obviously GPT. And what am I meant to do with the fact that you didn’t bother to write this email?” Right?

Warzel: Absolutely.

Johnathan Nightingale: And then like the alternative is to say, “Well, screw it. I will never let GPT do that. It’s an insult when somebody does it to me; I’m not gonna do that to other people.” And from that place, this sort of entrench and say, I refuse to engage with these tools. And then you’re putting your refusal up against management pressure. And, it’s driving conflict that isn’t very helpful.

Warzel: When I hear, “Oh, these agents are filling up these contact forms; it’s creating a whole bunch of extra work.” The guy who’s been listening to people in Silicon Valley talk about this technology for a very long time says, “Yes, well; their solution to that is you need agents on both ends, because having agents on just one end is, you know, not balanced.” There’s this way in which I can see that. People are creating—it’s a very classic tech thing to create a bunch of problems and then offer a technological solution to the problem that you created.

Johnathan Nightingale: Yeah.

Warzel: That all adds to more problems down the line. I also think, though, that what I wanna highlight there is the way in which this creates these asymmetries and builds these little cracks and pieces of distrust. That seems like something that feels really important in the context of all of this going forward, if you are somebody who cares a lot about what you do and puts a lot of effort into these things.

And then you have a group of people who may also care, but they use these tools. And there’s not this standardization of work output. And you see somebody respond to your email with something general. I think it’s really interesting that it creates that fracture, based off of how AI-pilled you are or how excited you are about the technology. And that feels like a bigger problem than I think people are thinking about right now.

Melissa Nightingale: We’re seeing that play out across like technology right now. Where you’ve got folks who feel like maybe you’re being incredibly efficient, and you’ve got like 12 agents working for you, and you’re getting a ton of stuff done. And I think, Wow, what a go-getter. Or I think, You’re really fucking rude, and you don’t give a shit about your work or the impact to my organization on you sending garbage across as a transmission.

Johnathan Nightingale: Isn’t that interesting? Like, not from a culture war, “red team versus blue team” shit. But like: why? Like, why can so many people nod along to this idea of like, Oh yeah, when you get a GPT email, that feels rude. Like, That feels like the person didn’t care. Right. I thought these agents were supposed to be solving all kinds of problems. I thought they were more talented. They’re passing the LSATs. They’re like, you know—they’re doctors, they’re therapists, they’re whatever. Like, why would we receive it as rude?

It turns out that humans really care about doing work they believe in, with people they care about. And when you hollow those things out, people have these emotional responses to it that I don’t see predicted by the marketing materials from the AI companies.

Melissa Nightingale: And the hyper-rationalists will fall short on this one every time. Because, fundamentally, being more efficient should, like, it goes—

Johnathan Nightingale: You ought.

Melissa Nightingale: You ought to be excited about being 10 times more productive than you were yesterday. You ought to be excited that your colleagues sent you an email that they didn’t spend any time on, because you also don’t have to spend any time on reading it or consuming it. Like, that should be exciting.

Warzel: You’re both management and leadership trainers. Which means your job is ostensibly to try to make people better bosses, right? And I wanna ground some of this in asking: What makes a good manager? Or what makes a good middle manager? What are those qualities there?

Melissa Nightingale: We have bosses who show up in programs. And they’re like, “I am a good manager because my team likes me.” Wrong. “I am a good manager because, like …

Johnathan and Melissa Nightingale: “My team is happy.”

Melissa Nightingale: We’re like, “Wrong.” Happy is an impermanent state, right?

Johnathan Nightingale: And you can’t take custody for people’s emotions.

Melissa Nightingale: No. Fundamentally, you are a good manager if you are making your team more effective.

Johnathan Nightingale: And effective feels really mercenary, but it isn’t. Because it turns out as you get deeper into this, you learn that the best way to build an effective team is to see them as individuals: to align their personal motivations and aspirations and sense of mastery, the things they want to learn, their curiosity with the things your organization is trying to get done. It turns out that, like, that only happens if there’s a high level of psychological safety. If they’re able to take risks; if they’re able to talk to you about their struggles.

Melissa Nightingale: If you’re able to give critical feedback on the work, where it is showing up exactly as it should and where it isn’t showing up exactly as it should.

Johnathan Nightingale: And if they see you engaging as an authentic leader. They don’t need you to be perfect, but they need you to not be bullshit, right? It’s an important part of how they cohere as a team, and how they find anything that you have to say remotely credible. But many people in management roles lack those skills. And if you’re like, “Wouldn’t that make work terrible for a lot of people?” Yes.

Warzel: There we go. Well, part of the reason I ask is because it seems in this AI conversation, the term management is a skill set that AI companies seem to want to impose on all of us, right? Recently the co-founder of Anthropic, Jack Clark, went on a podcast, he’s talking about the way that chatbots and increasingly these coding agents are, you know, going to be sent off to accomplish these tasks. And there’s going to be all of what we’re talking about, right? These things happening on behalf of us: goose chases, all kinds of stuff. And he had this quote that I thought was striking. It’s one of the reasons I wanted to have this conversation with you all. Which is, he says, quote, “Everyone becomes a manager, and the thing that is increasingly limited—or the thing that’s going to be the slowest part—is having good taste and intuitions about what to do next.” What do you make of that line? “Everyone becomes a manager.”

Johnathan Nightingale: It’s such a shallow read on management, isn’t it? Like, if you think about it—let’s say he’s right. Let’s say he’s right that when I fire up my Claude Code instance and I say, “Claude, create a marketing team for me. I want a content marketer. Want somebody on social media.” Right. Have I done it now? Like, can I transfer those skills over to the humans that are still on my team? Is it the same thing? Can I just go to Tony and be, like, “Tony, get Alex and Sam in a room? You got new jobs. Now. Here’s what you’re doing.”

Is that going to work? Nobody thinks that’s going to work.

Melissa Nightingale: I also think any model for management that doesn’t come with employees who have needs and, like, labor and rights—there’s a bunch of pieces that are missing from that mental model. And either that’s accidental, or that’s on purpose. But we should all be really concerned about a model of labor and a model of management that includes work happening without any capacity for what the people doing that work—or what the folks who are supposed to be responsible for that output—need.

Johnathan Nightingale: Buddy seems to know a lot about AI. I know the podcast you’re talking about. It’s cool. He’s built something that’s very big and seems to be changing a lot of people’s lives. And, I hope, some of them for the better. Like, that’s super neat. But on management, I’m not convinced he has the range to give anybody advice on what constitutes good management. You can build a very wealthy company and still be cooking a bunch of people inside it. And saying something like that—I don’t know, you can call that an insult, you can call that a threat, but that’s not what management is.

Warzel: Well, what’s interesting is, you know: As you’re describing what makes a good manager, and you pause and say, “This could sound mercenary.” Right? But what’s actually involved in all of this is the very human work of recognition. Of getting to know people. Of caring. Of giving a shit, right? It seems like that idea of “everyone becomes a manager”—that definition from an AI executive—it pauses at the mercenary point. It says, “He’s with you until that moment where you say, But then it requires all this.”

And part of the reason why I want to have this part of the conversation is also because my partner, Anne Helen Petersen, and I wrote this book about the rise of remote work in 2020. We spoke to you guys a lot about that book. And one of my broader takeaways from all the reporting is that—despite being in the boss layer, right?—the managers and especially middle managers were pretty miserable. Just in general. Just, like, a pretty miserable, core of that thing. Like, maybe miserable in different and unique ways than, you like oppressed rank-and-file workers. But pretty miserable. S

So when I hear that we’re all gonna become managers? From that, I hear: Man, that’s a lot of task switching and a lot of, “I’m getting incoming from two sides of this thing.” Like, two groups of people are kind of converging on me. I’ve got these unhappy people on one side; this unhappy thing on the other side. I kind of have to figure out how to exist in this world. I’m being pulled in a hundred directions.

Melissa Nightingale: Charlie, you’re selling it. You’re making it sound so compelling.

Johnathan Nightingale: Strong pitch, strong pitch.

Warzel: But that, to me, is like: I don’t know. I mean, does it seem as dystopian to you? Or do you just recognize this as, I don’t know, a guy pontificating? Without, as you said, the understanding?

Melissa Nightingale: We have a working mental model; like, we have a real-world model for where automation takes more of the front seat on management. Amazon warehouses are a good example. Uber drivers are a good example.

Johnathan Nightingale: Already being managed by algorithms. The common thread there is this idea that where people are working in Amazon warehouses because they can’t automate that piece yet. Right. And so they build all the automation around these little stations where the human stands, and the humans are reaching up and reaching down. That shouldn’t be our vision for the future of work. And when you listen to a lot of the people who are like, “Oh, everyone’s going to be a manager.” You’re to have this swarm of agents. Who’s doing stuff? Like, what’s the end state there? That you’re a team of one? That you’re a company of one? And so, when you try and sell me this story about a billion-dollar company with one person, I’m like: Think about the best times you’ve had at work. Best times. You might have had a shit boss. I get it. There’s a lot of them. We’re working as hard as we can. But, like, the best times you’ve had at work—and I guarantee that story involves colleagues. Right? And so when somebody tries to sell you on, “Don’t worry; you don’t need colleagues anymore,” I’m like: What are you doing? Like, that’s an anti-signal. I understand your technology is very impressive, but, like, that’s a weird thing to sell.

Melissa Nightingale: Unless you’re annoyed at paying the junior engineers $300,000 a year straight out of school. And then it’s a very compelling sell.

Warzel: There’s a lot here, right? Some of these people who are talking this … some of them, yes, are people who are inside large companies right now that are building all this. That have this workforce. So I think that argument makes a lot of sense. There’s another group, though, of, let’s just say “venture capitalists” who are actually on that island, right? A little bit. I mean, yes; there are plenty of people who work in some of these venture firms, no doubt. But the idea is that sort of like, life of the mind. Like “I’m this tech soothsayer.” And I think in some sense there is this, “How can I push this to the furthest possible extent?” Right? And there’s this idea, always, with the efficiency, right? The reason why the AI bro–type person who’s saying this thing about the excitement of the first one-person, you know, unicorn company, I think, speaks to the idea of … like, this is “efficiency” pushed to its broadest level, right? This is like the cheat code for late-stage capitalism.

And I think it ties though to this broader premise of how productive this stuff actually is, right? So there’s this recent survey from this company called ActiveTrack. And they analyzed over 10,000 workers across 376 companies. And they did it 180 days before and after AI adoption. And the thing that I think won’t be surprising to a lot of people who follow this is: email, up 104 percent. Chat and messaging, up 145 percent. Collaboration time surged 34 percent to an hour a day. Multitasking rose 12 percent. It’s that classic, you know, Parkinson’s-law, “work expands to fill the time available for its completion”–type thing. What do you make of those types of numbers and the idea of productivity?

Melissa Nightingale: We tell bosses all the time: Busy is not the same as effective. Like, you can run your team totally ragged in terms of having them chase every idea that seems like a good idea. But if that’s not what we’re here to do, then you’re wasting their time and your own.

Johnathan Nightingale: Yeah, the maximalist arguments are always so weird, right? Like, the thing you could do is say to your team: “This is a cool tool; we should figure out where we can apply it.”

Melissa Nightingale: Where is there an annoying problem within the organization that you wish someone would fix for you? Where is there an internal tooling thing that would be so cool to have and get a thing out of your way in your workflow? Like, great—let’s go build that.

Warzel: Right. Software-size problems.

Johnathan Nightingale: That could be the end of a sentence. It doesn’t have to be. And then we fire everyone. Like, it doesn’t. You can just end. They’re like, “Well, but if all your competitors are cutting to the bone and outsourcing all their sort of, you know, friendships to ChatGPT or whatever, then you’re going to have margin pressure. And you’re going to have to do the same thing.” And I’m like, man, “Maybe.” But it turns out that creative, resourceful, adaptable humans are good at some shit. And that an LLM—which however amazing you might find it to be—is trained on yesterday. It’s at some point going to run into problems inventing tomorrow, right? And like, that’s a thing people can do. And then tomorrow it’ll train on it. But I will bet on people. Again, not like a team thing. It’s cool for the people to have tools. “We’ve got lots of tools.” That’s great.

But it’s so weird to bet your business on entirely outsourcing critical thought, creativity, collaboration, partnership to this thing that can generate grammatically correct paragraphs. Like, it just feels like such a weak-sauce version of leadership.

Warzel: How hard has it been to give that message to this group of people? Have you been effective in conveying that? Is the siren song of all of this, you know, too difficult to resist? Like, what are you butting up against with this?

Melissa Nightingale: Two things. Okay, so it’s a great question. Like, on the one hand, you spend a third of your waking hours at work. If you’re lucky and have like a normal work schedule, you spend a third of your waking hours at work. So I think for a large number of people, the idea that like one—we just fully and outright reject the idea that that’s how we’re going to spend a third of our waking hours, as a collective. Like, absolutely not.

Two, we’ve seen it, and that lends some credibility. In that we’ve seen inside a lot of organizations, and we talk to a lot of leaders about moments at work that really mattered to them. And it’s like: I think the conventional wisdom is nobody would have any moments at work that mattered to them. Nobody would have any moments where a boss saw them, connected with them, brought them up, helped skill them up. Helped unlock the next stage of their career, because work is crappy. We have to spend a third of our life there, and it’s always going to be crappy. But the fact of the matter is, you ask people: Do you have one of these moments? Do you have one of these things that happened where work really mattered to you, or was a support or a stability for you at a time where the rest of your life was, like, really rocky? People, by and large, do. And so our starting point, I think, for a lot of folks is that the idea that it could be good for a lot of folks is one, a radical concept, and two, a very welcome idea.

Johnathan Nightingale: But when you ask about receptiveness, it’s funny. One of the first companies we ever worked with was an AI company. And I remember meeting with the leaders that were going to be coming through a program with us. And this one guy, very sort of eccentric-professor vibes when he came in. Sort of scattered, came in a couple of minutes late. And he said, you know, “I’m coming to this management program. They’re sending everybody to this management program. But I need you to know something right up front. I don’t believe any human should manage any other human.”

Warzel: Yeah.

Johnathan Nightingale: Cool, fair, yeah, great. He’s a bit, “I’ve never done a program like this before; so you know, I’m open to it. I just want you to know that upfront.” By like the third week of the program, he’s sitting there reading High Output Management by Andy Grove. Which is sort of, former CEO of Intel; like a standard management text, particularly in tech circles. We’re talking about hiring, and he’s looking at a job description. And he’s like, there’s a bunch of gendered stuff in that job description. You’re going to end up with a really tilted candidate pool if you keep doing it. Like, he’s fully engaged with it, and is really thoughtful and conscientious about how to engage with it. He just didn’t know the receptiveness is a really easy sell. It’s a surprisingly easy sell. Nobody likes to be in a job that they don’t know how to do and feel like they’re failing all the time. And if you can give them some stuff, you know, there’s this moment where you give them some tools. And they’re like, “I don’t know if that’s going to work.” And then you get them back next week, and they’re like, “That did work. What else do you have?” Right. And like, it’s actually really easy to convince.

Warzel: How worried, just hearing you say this, how worried are you guys that these tools, these AI tools, will effectively just act as a Band-Aid for any of these moments? Of “Instead of having to think about it hard, and have that conversation that’s ultimately really fruitful and ultimately helps me and everyone else around, I’ll press this button instead”?

Melissa Nightingale: We come back around again, right? It’s like, if I am your direct report and I fucked up in a meeting, like: I’m sorry, I just didn’t know that thing, and I said that thing, and I thought it was a good idea at the time. But like, whatever, I screw up in a meeting. And what happens after that meeting is you send me a thing to tell me I screwed up in that meeting, and it is perfectly outlined.

Johnathan Nightingale: Lots of em dashes.

Melissa Nightingale: It is perfectly structured. And, you know, you’ve given the feedback to an LLM, but it spit out a thing. And then I get the thing; we’re back to the part where I’m like, That’s rude as shit. Like, if I screw up, tell me. I am a grown-up; I can absolutely handle it.

But you’re back to this weird moment in work culture right now. Well, either that’s a well-intentioned manager trying to format a thing so that it lands correctly without having to, like, have the like social risk in that moment. Of, like, “If I send it to Melissa and she’s upset about it … well, if GPT wrote it, she’s mad at GPT. She’s not mad at me. But if I actually put time and effort and energy into it, I might get it wrong. It might not land well. And I might have to spend some time reflecting on, like, That isn’t the way I wanted that to go. I want it to go differently next time.”

Johnathan Nightingale: There’s this study. Even if it never touches the employee, even if it’s just something that the manager does, you know, they go into their own chat window and say, “Here’s what happened. What am I supposed to think about it?” Study came out a little while ago, talking about sycophancy in LLM chats and its effect on sort of attribution of fault during conflict. Right?

So I get into a fight with someone, or my direct report is pissed off because they didn’t get a promotion. Or I’ve got hard feedback to give to them, and I gave them the feedback, but it didn’t go the way I wanted it to. And so I’m using Chat to help me debug it. And what the study found is that the more sycophantic the LLM is, the more likely I am to feel like I did nothing wrong. The more likely I am to bring that sense that I did nothing wrong into my future interactions with that person. And then you cross-multiply with the studies that are well established now, that LLM use suppresses critical thought and critical reflection. And that a major component for leadership development is critical thought and critical reflection. And you’re in a bad spot. Even if the employee never receives that GPT message, just me using GPT as my leadership coach is likely to really impair my sense of my relationship with my people, and also my own reflection.

Melissa Nightingale: Outside of management and leadership circles, it may not be obvious why that’s such a core component. But basically: If you are in a modern organization today, one of the biggest problems that we have of getting bosses to show up differently in the role is that they are often running from meeting to meeting to meeting to meeting to meeting. So if something goes wrong in my first meeting of the day, I have no opportunity—other than 2 a.m. when I’m staring at the ceiling—to think about, like, How did that go, and what do I want to have happen next time? Learning like humans are really freaking good at like: “This went this way; like I touched the hot stove. I don’t want to touch the hot stove again. And here’s what I’m going to do differently.”

If they’ve got time to think about it. The hard part that we have, in our industry and in our sort of line of work, is that for many leaders there’s not any of that baked in anymore.

Warzel: I want to get here, near the end, of something bigger, though. That we’re kind of circling around all this. Which is: this idea of a constant replacement in work, right? Replacing the expectations of how much work should take up someone’s life. You know, the expectations of how much dignity someone should be able to derive from it; the expectations of the path of predictable progress in a given career. The technology is often that we put into these spaces, you know, as we said. They free up space that is then used to, you know, fill more in. You keep piling stuff on here, without the attention and as much of the focus on the nourishing qualities that we’re talking about here. And the things that might give people some purchase and some connection. And you’ve all been writing a little bit around this idea lately of social atrophy, and the role that work plays. What is work’s role right now in this broader loneliness epidemic? Third-space dwindling, broader-disconnection feeling that a lot of people are experiencing?

Melissa Nightingale: We started to see weird glimmers about two years ago. Where a lot of organizations were saying, like: “I’m managing a team, but my team is geo-distributed, right. And so, I’m managing people all over the world. And sometimes I’m managing them, occasionally in office, but sometimes I’m managing them [remotely] … and we just don’t share a lot of overlapping daylight hours. And we work in sort of our own Zoom windows. And for my folks, where I’m managing them, and they’re not interacting with a lot of people, things have gone a little bit weird. And what do I do about that?”

Like as a management question, right? Would come into our programs and say, like, “It’s not a performance problem, per se. They’re showing up for meetings. Like, the camera’s off, but they’re showing up. Things have just gotten wobbly enough that I have an overarching wellness concern. What do I do with that?”

Johnathan Nightingale: And the more we looked at it, the more we saw … you know, Melissa uses this language of work as the last bastion. Robert Putnam wrote Bowling Alone, right, and talked about “People aren’t in bowling leagues anymore, but they also aren’t in rotary clubs, and they also aren’t in churches.” That whole sense of, like, our community glue is, you know, eroding. If you want to take the worst version of it. Or certainly evolving.

But through all of it—work is a place that you show up, and you’re around other people. And, you know, they see you and appreciate you when you do good things. And give you interesting things to work on. Or at least give you interesting things to talk about while you’re getting coffee. When that falls apart, there isn’t another backstop. There isn’t another place we spend eight hours a day, five days a week.

Warzel: So you feel like these tools, as they’re further embedded in the workforce—especially if they’re embedded, you know, not critically—are a real threat to that.

Melissa Nightingale: I think if we had community answers for human connection, I would be less worried. But we have eroded most of our social answers that are baked in. We don’t live near our relatives anymore. Most of us sort of go away. And then we sort of set up new communities. And maybe we’ve got some chosen family. But we have a really different context. And our backstop—for a lot of us, sort of last bastion—was work. Where we had to go, and we had to socialize. And even when we didn’t feel like it, we had to, like, put on our hard pants and get ourselves sorted. And, you know, do the thing. And humans are social creatures. Like, it is core to who we are, the whole way along.

Warzel: I fully agree with that. And yet I wanna push back slightly, because I can imagine there’s people listening here who are going to say: “Work is work. Work is not family; work should be transactional.”

Johnathan and Melissa Nightingale: Totally. Yeah.

Warzel: And these AI tools depersonalizing work in some way—in making it so that like, yeah, when Tony sends that email, and it’s very clear that he doesn’t care, because it’s a chatbot—ultimately, that may be even a better thing, right? Or these tools are going to free people up to not have that time. I think we’ve sort of debunked that part of it.

But this idea that impersonalization is actually a feature, not a bug, right? That these companies … we were talking earlier about Amazon warehouses and things like that. One of the rebuttals to that from the AI-evangelist guy on X.com is gonna be like, “Who cares, man? It’s a business. We’re supposed to wring out every inch of productivity, or whatever. And yeah, there’ll be more bots in the chain, so that we don’t have to hang up ibuprofen because people have repetitive-stress injuries.”

This is sort of the true mercenary level. But also the mercenary level, I think, on the sense of employees who are like, “I’ve had it. I’ve been exploited by the system for so long. I actually like the idea that this is going to feel depersonalized.” How do you see that butting up against the last-bastion status?

Melissa Nightingale: We meet a lot of those folks. We meet a lot of folks who are like, “I just don’t care anymore. I have cared a lot. And I really feel like I’m ready to care less.”

It’s hard. And the reality for those folks is … it’s tricky. You can put yourself into a role in an organization. That you think you’ll be fine. And like, you will still manage to get yourself promoted. And they will still figure out that you’ve got ideas, and you will still find your way to … like, they often find their way back to, “Okay, I do care about this. I don’t necessarily need it to be like my entire waking hours, or my entire personality. I need some space from it, and some other elements in play.”

But it’s hard. It’s very hard. A lot of folks have work as a key component, and a core element, of their identity. And you can say, “Well, they shouldn’t. Like, they’re silly; they’re foolish for feeling like that’s a moment of profound identity shift.” But again, we have to work with humans as they are, and not as we wish them to be. I think it’s okay that people care about their work.

Johnathan Nightingale: Yeah, when you hear that—have boundaries. Get out of toxic workplaces, right? Because nobody’s saying “Wherever you are, that’s where you must be forever. Otherwise, you’re ungrateful. Otherwise, you’re not applying yourself.” Like, that’s foolish. Like, if you need to get out, get out. If you need to keep yourself safe, keep yourself safe. But, in a deeper sense, I don’t believe you. Like, we do actually care about this shit, and so, like, if you don’t care about your job, that’s fair. Do whatever you need to do. Capitalism’s mean, right? But, you will not sell me on “Nobody cares about their jobs” or that it’s not worth caring about your job. Because so many of the people we find who draw so much meaning from it don’t see themselves in that at all.

Warzel: So to end then, with that in mind, how does that intersect with this idea that, you know, these AI tools are going to destroy knowledge work or white-collar work or whatever? Right? Like, is that a bulwark against it? The idea that there’s a lot of people out there that fundamentally give a shit? Like, ’cause it feels to me, if that part is really true, you’re going to have this technology come right up against people, like a major pillar of who they are, right? And I don’t think that there is a sense that yes, capitalism can sort of just, you know, knock people over, bend people to their whims. But I also think that, it seems to me, like this is all geared to meet some really heavy resistance from people who work. Do you think that’s true?

Melissa Nightingale: Remember that protest looks a lot of different ways. But like, me feeling like, as an employee, I’ve got options in terms of where I work. And who my colleagues are, and whether I have colleagues at all. Means that organizations that sort of lend themselves to that—or sort of specifically go out with a message that says, like: This is what we’re doing. We’re gonna have colleagues. It’s gonna be great. You’re gonna love it. Like you’re gonna be in an occasional meeting that isn’t useful. It’ll be okay.

Johnathan Nightingale: But there’ll be small talk beforehand. And nobody likes small talk. But it is interesting to see, you know, how her vacation went and stuff.

Melissa Nightingale: But like, you will see change, I think. Less through walkouts and more through people feeling like the pendulum swings back, and organizations are trying to hire again. And AI companies, in particular, are very skilled at what it looks like to have a very hot talent market and to have to compete on the merits of the organization.

Johnathan Nightingale: Isn’t that wild? That while they’re telling everybody else to lay off your team, and pay the remaining ones as little as possible for doing 10 people’s worth of work.

Melissa Nightingale: They are having 2021’s version of the labor market.

Johnathan Nightingale: Like, just throw any amount of money at getting top talent. We need the right people in the door, otherwise we’re not going to be able to build the future. Like, what? I thought Claude was doing that.

Warzel: Melissa and Johnathan, thank you so much for coming on Galaxy Brain and talking about the weird future of what we all do.

Johnathan Nightingale: Anytime.

Melissa Nightingale: This was a lot of fun. Thank you.

Johnathan Nightingale: Thank you.

[Music]

Warzel: That’s it for us here. Thank you again to my guests, Johnathan and Melissa Nightingale. If you liked what you saw, new episodes of Galaxy Brain drop every Friday. You can subscribe on the Atlantic YouTube channel, or on Apple or Spotify or wherever it is that you get your podcasts. And if you wanna support this work and the work of my colleagues, you can subscribe to the publication at TheAtlantic.com/Listener. That’s TheAtlantic.com/Listener. Thanks so much, and I’ll see you on the internet.

This episode of Galaxy Brain was produced by Renee Klahr and engineered by Miguel Carrascal. Our theme is by Rob Smierciak. Claudine Ebeid is the executive producer of Atlantic audio, and Andrea Valdez is our managing editor.