Meta Cut 8,000 People. It Has Nothing To Do With AI Working.

I think we're getting the story on AI layoffs wrong. AI layoffs are being used as a generic term for everything and it's just killing me. That is not how it should work. AI layoffs are being used simultaneously as a as an excuse for people who are experiencing frankly a local recession in their sectors and as an excuse by people who are spending on GPUs and as an excuse by people who don't know what to do and need an AI story. So in this video we are going to break apart this AI layoffs label this big phenomenon. We're going to talk about what's in the box because I think if you are a leader, what you can learn from AI layoffs is one, how to not do layoffs like this badly, but two, much more importantly, how to understand where the market is going so you can form a strategic perspective based on the fairly obvious strategy signifier these layoffs are showing. Because, by the way, there is no more highstake strategy signifier than a big layoff. They are telling you publicly where they're going. So, if you're in any kind of leadership role, this is free intelligence for you. Two, we're going to talk about it from a job search perspective. How do you look at it if you've been laid off, if you're going to be laid off, and how do you think about this is where I need to go. This is the next company I need to target. This is how I don't want to screw up where I'm going to target because I want you to have that perspective. Again, it's intelligence that you should take. And I don't think you get that intelligence if you just look at this as one big block. My next piece is just for those of you who have been laid off. I've been through this, too. I want to give you a special offer for all of my media so that you can get all of the detailed posts, the detailed guides. I know there's a lot of rich material in there that you can go after and use to build up your skills for what's next. I want to make sure you have that. So, I'm offering 50% off um a year of Nate's newsletter to get you back on your feast and wherever you want to go next. Uh access to all of my previous posts. if that's something that's interesting to you or to someone you know who's been laid off. Feel free to share this URL with them. Um and they can sign up and or you can sign up and uh we want to make it easy. We want to make it something that you can grab this and go forward uh with your life, go forward with what you're trying to do um on your terms with AI, which is what this channel is all about. So, if that's interesting to you, go and grab it. Share it with someone who you know who's affected. I think one of the sad things about this moment is that every single one of us knows someone affected by layoffs right now in tech or out of tech. And so I want it to be something where folks know about this and know that there's AI support for them uh where it's needed. So grab that and uh best of luck. I know you got this. Okay, let's get back to it. The first category of AI layoffs I want to talk about is the big hyperscalers. Meta is the classic example here. Meta has been investing in AI for a while. They've obviously spent huge money on their top tier AI talent, but they are also laying people off like crazy. I think 8,000 was the most recent number. I frankly am in a mood where I expect every couple of months to hear about more AI layoffs at Meta specifically right now. What is Meta doing? Is this a story where Meta is saying, "We've already done so much with AI, we need less people." That may be what they hope you believe, but if you look underneath the covers, I think you see a more complicated story. This is based on me talking with folks at Meta who are individual contributors and also based on the publicly available reporting about Meta's culture and also based on their publicly available P&L spent. One, Meta is a great example of the kind of AI layoff that is shaped by their spending and investment picture and also by their culture. It's both in the same. The spending and investment picture is one of massive capital expenditure on GPUs. They are spending so much. They are building gigantic data centers and they do not necessarily want to only show a picture of massive spend to the market especially when they are not a market leader on AI. It has been a long long time since Llama was a market leader at anything. And it has gotten so bad that Meta has started talking and leaking about what their plan B is if they cannot catch up which reader I don't think they can. And if they can't catch up, they are apparently going to just start selling compute and be a cloud compute provider and that will be their thing. Sort of like XAI selling to Enthropic. When you are spending that much, here's the kicker. You want a story around operating expenses for the market that is positive that shows the benefits of AI transformation, particularly if you don't have a market leading AI and you're literally having to use claw internally, not llama, hence the layoffs. But this also aligns with Meta's culture. And that's the other thing I want to call out here is Meta has had and this is from uh a lot of stories that are well sourced and also from individuals that I've talked to and known at Meta very closely. It's kind of a dog eat dog culture. It is very much a you have to go after and take care of yourself kind of a culture. And in that world, you are going to be expected to manage folks out. You are going to be expected to make sure that you are one of the top you know 90% and not the bottom 10 or 20% in any given year. So you avoid that kind of cut. And when the cut comes, when they start to pick, they're going to start to pick based on that tearing. They're going to start to go after people they perceive as maybe not succeeding as aggressively as those around them. But but here's the thing. Put the toxic mix together with me. You have massive expense on GPUs. You have your own model not doing well. You have a desperate grab for Claude. And by the way, they're putting Claude leaderboards up with with tokens where you can say, "I'm spending more tokens than my buddy." and you have a ranking system, what that leads to is gaming the system so that you spend lots and lots on tokens and that doesn't lead to outcomes. So the takeaway if you're a leader and you're not at meta is really simple. Hyperscalers are desperate to make the capex work and that means that they are going to be doing anything they can to extend the utility of the market value they're providing. And that explains a lot of how these big players are acting in business competition right now. That is why there's such a big push laterally on corporate strategy from hyperscalers and big players. They need to take more territory so they can defend their valuations, right? Uh and so OpenAI is doing that. Anthropic is doing that. Uh you see the same play for Meta right now with the way they're pushing out and they're trying to show we can be a compute provider. They're trying to show that they have world models that work. They're trying to offer like an ecosystem model with Llama that is compelling from an open source perspective. They're also trying to get the next frontier model, etc., etc. This is not a strategy everyone can copy, but it is showing frankly weakness that other folks can pay attention to because the more you spread yourself, the more someone who is focused can dive deep and deliver value. And that's something that I think we need to take more seriously when we are talking about companies that are at a scale where they can focus on one thing. If you're a job seeker, I would encourage you to look real carefully at these big hyperscalers and ask yourself, do you want to be in a position where you are in that individual pecking order battle to not get laid off? Because if you find a job there, how do you know you're not going to be the next one laid off, right? Like that's one of the things that you have to sort of legitimately consider is are you being hired? And if you're being hired, which they sometimes do regret rehires where they have to rehire for talent because they fired too many people, how long is it going to be before they weigh you versus a GPU and decide they need to keep investing in the GPUs? That is a hyperscaler story. That is not the only AI layoff story in the market. We're going to get to some others as well. Let's start with the the Jack Dorsey and Block story next. That's number two. This is a case where you have a visionary leader. I call it the AI vision layoffs. It's a visionary leader and they are going to do what they are going to do because they need to rethink AI from the ground up. And so there's going to be a big layoff. Block did this. I think Coinbase has done this. There's a few of these out in the market where they have visionary leaders and they're just going to go after it. In that world, the key takeaway if you are a leader is real simple. Are you thinking systematically about AI implications or are you not? And I want to unpack Jack and and and the block layoffs a little bit here. Fundamentally, I think Jack did one thing really, really well. And I think there's something else he needs to do more of if he's going to be successful. And we need to acknowledge both of those in order to get this right. Because, by the way, even though layoffs are really tough, one thing that we have to call out is that Jack did a great job of genuinely grappling with the implications of AI for his company. Maybe he didn't grapple correctly, but he took it seriously. And that is something that I see with him and with other visionary leaders where they recognize that the firm is changing. You know, when we had electricity in the tens and 20s, we didn't know how to build our factories around it yet. It was difficult to optimize for greater outcomes at the factory level because we didn't know. And so we were trying to increase the the capability of individual workers without figuring out how to get to the factory output goals that we were talking about because we hadn't reject the whole factory around this new technology. We're in a similar position now. Jack is at least grappling with that. He writes out this idea that the firm itself is becoming intelligent. You have to restructure around that. I appreciate that. I respect it. I think it's a good thesis. But what he hasn't gone far enough at is thinking through the human implications and change management implications of this. He he gestures a bit at the new roles. I appreciate that. But I think that we need to go farther at understanding the human implications of this change in order to be successful. And so one of the things I would call out if you are a leader and you are not a hyperscaler which is most of us and you're thinking about this ask yourself first have you taken the idea that the firm is going to change seriously and if you have you done the disciplined thinking to understand and form a perspective on how that's happening for you and then and then third and this is the part Jack didn't do have you taken the time to think through the human implications and the change management implications at a high degree of detail and I think it's very difficult to do that without you individually understanding and spending time in the tech. If you are if you are afraid of code as a leader it is going to be really difficult to make it. If you're afraid of getting technical it's going to be difficult to make it. You have to not be afraid to sit down and understand how claude code works by actually coding something or how codeex works by coding something and putting it together. I if you're scared of that, it's going to be difficult for you to envision the scale of workflow changes that we're talking about. If you can't describe an agentic pipeline in your own words, you're going to have some trouble. And so when I think about the lesson of Jack and what we can learn from Jack, I think it is primarily about how do we take that vision and pull it forward for humans? How do we understand how humans can become effective partners with AI in the firm and think really deliberately about that? If you are a job seeker and you are looking for a role at a place with a visionary founder, you should ask yourself, has this visionary founder staked out a position on AI yet? The answer at this point is probably yes. If they have, are they clear enough about the human implications that I can go and sign up and say, I'm excited for this vision or have they not been clear about that yet? And then you have to ask yourself, are they going to get clear? Am I ready for the ambiguity that that is that that's going to imply for my role? And I also think yes there are a few people who are visionary in certain aspects of life in certain aspects of business who may not have quite formulated their opinion on AI. Be very careful if you are applying for work at a place like that where there's a strong founder and you're not sure if they have a clear vision on AI in that situation. They will form one eventually sooner than later and you may be impacted just as those folks at block work and that's something that I you're just going to have that happen with this visionary layoff. So, we've talked about two, right? We've talked about meta and the hyperscaler layoff phenomenon. We've talked about Jack and we've talked about this idea of a visionary layoff phenomenon and what that looks like. I want to talk about uh a third one. I want to talk about Cloudflare and the idea of a usagebased or activity based layoff, which is very much what they said when they did their layoffs recently. It was 600% usage is up. I have heard since that they are doing regret rehires, which we've seen with CLA in the past. Regardless of the story on the inside, the thing that I want to call out is that these companies need to pull the lever to show transformation with AI and that if you are doing it on the basis of activity, you're doing it incorrectly. You need to do it on the basis of outcome. And so there are going to be a lot more stories in 2026 where people talk about and say, "We've got this utility. We've got this activity and usage is up. This is great. We've got dashboards showing tokens are being burned by the billion." So, what about your outcomes? How does that how does that help you shape your outcomes? If you can't say that and show that and design for it, then you're going to be in a very unstable position. And if you're a business leader and you're looking around your space and you see people doing this AI layoff lever and talking about their usage and you are tempted to do a meto approach, which I know people who are tempted by this, don't do it because the usage they are talking about is unlikely to result in outcomes unless they have deliberately aligned their organization toward outcomes. And if they had done that, they would be talking about outcomes when they fired people because they would have outcomes they were going after and they would be making a hard decision, but they would talk strategically and coherently about what they were going after, which does sometimes happen. But most of these people who are out here doing activity- based layoffs are just trying to tell a story to the market and they're trying to get the market to believe that just using AIM more as an individual magically results in extended productivity for the firm. It does not. And you cannot sit there and assume a linear extrapolation from last year's behavior with AI, from last year's individual productivity with AI to this year and say we're doing more productivity. We're using the 2025 ways and it's going to work. That that's kind of what Uber's been doing. So Uber has famously or infamously leaked that they're frustrated with their clawed budget for this year and they feel like it's an overspend, etc. If you are if you are comparing your budget in AI with last year, you're doing the wrong thing. AI was a different beast last year from a corporate perspective. The individual productivity may have been there a bit, but it was not nearly the kind of firm moving deep agentic pipeline longunning agents in production phenomenon that it is today. It just wasn't the same thing. And you can't complain about your budget if you have an entirely different tool. And that's really what you have with AI today. But people haven't figured that out. They still expect and mentally model this individual productivity activity matrix as like this is the thing. If I have all of my teams report 100% usage and they're using it for two hours a day like then I will get my thing done. People do that because they don't understand how to model the value through their firm assess for outputs and go back and say what is an agentic pipeline that delivers on that and how can I help put humans above the loop not in the loop to deliver it. And that is something that is very rare. And so when you see these activity layoffs, if I'm a strategist at another company, I view them as signs of distress. Something is not going right. They did not plan well. Think about that as an opportunity. If you're a job seeker, view it as a stay away sign. And I think a lot of people do, but I'm just going to underline it. Do not trust a firm that is using AI activity as a big like we're adopting AI. Don't do it. Just don't trust them. The fourth category, what I'm calling a hopebased layoff. Uh, a good example of that, I think, is Cisco. Sometimes you need to tell a story to the markets about AI, but you don't have an eyepopping stat necessarily that you can support it with. You have a narrative. And the narrative uh may be around back office operations. It may be around efficiency and delivering for customers. Uh, and if you're a tech company, you want to show at this point in the AI revolution that you have you have impact for AI, that you have not just wasted the last two years, but you don't necessarily have a comprehensive vision of how AI transforms the firm like Jack. You don't necessarily have eyepopping usage statistics to base that off of like Cloudflare. You're not a hyperscaler, so you're not investing in GPUs like Meta. You just need to tell a story that helps the markets understand where you want to go. And I get that you need to tell a a transformation story. I think my concern is for firms that are telling that story. I I understand that you get a pop in the markets right now when you do layoffs because it reduces opex. My concern is the long-term health of the firm is not what it needs to be if you are laying folks off and using AI as the hope lever in that story because long term you are going to need your best people to deliver on AI transformation and you don't know in advance which people you can afford to lose. And so my understanding with most of these stories that are light on numbers and big on narrative is that companies do not have a clear impactful outcome for AI yet. They need to tell a story in the markets and they turn to layoffs as a lever. Don't do that. That's not helpful. Um, and if you're a job seeker and you're seeing these layoffs and you're wondering like what is going on, those hopeclass layoffs are signs that a company is trying to find its way. It doesn't really necessarily have a comprehensive overall strategy on AI that has the backbone of a Dorsy like vision, but they know they need to get there and they don't quite have the puzzle pieces fit together yet. And frankly, people are paying the price for that. I want to encourage you again. If if it's a hopebased layoff situation and those folks end up rehiring, it's kind of like meta. Like you look at it, you say, "When are you going to fire people again?" Because you don't necessarily have that clarity on the long-term vision that you would need to give them confidence that they're going in the right direction. And if you're in the space and you're looking at a layoff like that, it kind of tells you, it's a very expensive signal in the market that basically says we need to tell an AI story very loudly right now. And you should ask yourself competitively, why does this company need to tell this AI story so loudly, so loudly that they need to do the layoff story before they fully have the AI piece baked out. I get that there's huge pressure from boards to do stuff. I get that there's pressure from Wall Street to do stuff on AI. I understand that. I talk to those folks. But if you don't have real clarity on the substance of what you're doing and you're just doing hope, you don't even have activity, you got a problem. So those are the four classes of layoffs, right? There's the hyperscaler class, there is the visionary leader class, there's the activity class, and there's the hope class. Most layoffs in 2026 in AI fit into one of those categories. The fifth one, by the way, is it's not about AI, it's about something else. And that is also a big category. It could be about we're not doing well in business. It could be about we overhired in the past. That is also a massive category and I just want to underline that. But that's not about AI. So it wasn't my focus here. So that's what's really going on. Those are lessons and takeaways for you as leaders, lessons for job seekers. And if you want to as a leader dive in and understand better what the implications are competitively for these types of layoffs, understand how to read these layoffs in your particular vertical. I've written up some specific stuff for you on the Substack about that as well. I would encourage you to dive in there because it goes much deeper than I can go in this video. For now, the key takeaway is please, please, please do not view an AI layoff story as the same as the next AI layoff story. I know it's tempting to. I see the websites that are tracking AI layoffs like they're one big phenomenon. Don't fall for it. They're not. Understand the deeper story. Okay, I will see you next time. We'll cover more AI news soon. Subscribe and share with your friends.