The AI-Panic Cycle—And What’s Actually Different Now

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And everybody whose industry is being destroyed by them is saying like, you're immiserating us while you're putting us out of work. I'm Charlie Worzel, and this is Galaxy Brain, a show where today we are going to calibrate our anxiety about AI. Because it's a weird moment right now in the world of AI. To put it bluntly, there are just a lot of people freaking out. And I think a big part of that freak out has to do with the rise of coding agents. I'll explain what that is, but first, I think it's important to go back a little bit. At the end of 2022, ChatGPT came out. And it suggested evidence that there is a paradigm shift. This moment when the utility of these large language models, which are trained off this unbelievable amount of questionably procured human data, it's a moment when those became more legible to people outside the tech industry. Chatbots allowed people to interact with these models like they would a human. As such, they were widely adopted by people and businesses for all kinds of tasks. Searching the web, writing essays, emails, replacing their therapists, automating all kinds of drudgery. And so we got hallucinations, and AI girlfriends, and slop. We also got a lot of people and companies relying on these tools to remove any and all friction from their lives. You had evangelists who saw these models get better at benchmark tests, and they speculated about whether real intelligence could ever spring from the tools. But you had others who saw them as basically just an advanced form of human mimicry, based off this corpus of stolen information and forced on society by big tech and venture capitalists who at the same time warned of a future where all these white collar jobs could go away. This winter, I think, marks the first paradigm shift in the AI world since the chatbots. And the reason for this is the arrival and deployment of coding agents. Agents like OpenAI's GPT 5.3 codecs and Anthropx Cloud Code. These agents are capable of automating many aspects of white collar work. The tools are less user-friendly than chatbots, but the results are often way more impressive. You can give them access to your computer or a given program. You can prompt them with a series of tasks, like clean out my inbox, pay my credit card bill, book me a flight to Fiji. Basically, they act like a personal assistant. And they go off, and they do it, often quite well. It's far from perfect, but it feels like a genuine step forward. And so, cue the freakout. In the last few weeks on platforms like X, where a lot of the AI discourse tends to happen, there's been an unbelievable amount of bluster about these AI agents, and the speed with which everything is changing. There's this feeling there that there is a gap between insiders and outsiders, and that that gap is widening. That the people who are using these coding agents are living in some kind of near future that most of the world just doesn't understand yet. And so you get a lot of posts like this one, from X's product lead Nikita Beer, quote, Prediction. In less than 90 days, all channels that we thought were safe from spam and automation will be so flooded that they will no longer be usable in any functional sense. iMessage, phone calls, Gmail. And we will have no way to stop it. You get people saying that they've built entire season-long podcasts in a weekend using the agents, or claiming that entire industries will soon be obsolete. And then, on February 10th, Matt Schumer, who is an AI executive, wrote this extremely long post on X. With the title, Something Big Is Happening. Now, this post went viral by just about any standard, and especially on X. In six days, it has more than 83 million views, according to the platform's own metrics. And the piece begins with a warning. Think back to February 2020. Schumer is comparing this moment with those days just before the world shut down due to COVID. The people shouting now about how AI is about to change absolutely everything are the equivalent to those people who were urging others to stock up on toilet paper in 2020. Quote, I am no longer needed for the actual technical work of my job, Schumer writes. And he ends the post ominously. Quote, I know the next two to five years are going to be disorienting in ways that most people aren't prepared for. This is already happening in my world. It's coming to yours. Now, Schumer's likely doing a few things here. One, he's talking his book. He's bought into the AI industry. He has at least some vested interest in where all of this is headed. The COVID comparison is what you might call a sensational framework, one that's clearly meant to strike at least some trepidation into people's minds. The post portrays the things the AI industry is building as civilizationally important to the point of being dangerous. That's just good marketing. On the other hand, Schumer's post is drafting off a few real feelings. You can see it in the backlash to the onslaught of AI ads at the Superbowl, in fears that the coding agents do represent a change in what these tools can do, in concerns about how much money people are investing in the AI boom, in worries about the speed and the adoption of these tools, in anxieties about whether they will actually disrupt employment. Now, these fears don't necessitate believing in AGI. And one doesn't have to be an AI evangelist to imagine that these industries looking to boost productivity or profits by any means necessary might adopt these tools in short-sighted ways that are going to hurt workers. It's precisely because of all these fears and evangelism that the AI conversation is extremely polarized. The hype is intense, it's occasionally absurd, and it's sometimes scary. But the change in the technology is also real. So how should we be thinking about AI in this moment? That's the reason I wanted to talk to Anil Dash. Anil has been working in tech for over 25 years. He is a prolific entrepreneur, he is a blogging pioneer, and he was an advisor to the White House Office of Digital Strategy in the Obama administration. Most importantly, he's been working with and participating in the world of coding long enough to see a whole bunch of boom and bust cycles in this tech world. He has a really nuanced view of large language models and AI tools, and also a sharp, critical eye for the industry at large. He joins me now to help us understand how to navigate this moment. But first, a quick break. The world moves fast. New workday? Even faster. Pitching products. Drafting reports. Analyzing data. Microsoft 365 Copilot is your AI assistant for work. Built into Word, Excel, PowerPoint, and other Microsoft 365 apps you use. Helping you quickly write, analyze, create, and summarize, so you can cut through clutter and clear a path to your best work. Learn more at Microsoft.com slash M365 Copilot. This episode is brought to you by Indeed. Stop waiting around for the perfect candidate. Instead, use Indeed Sponsored Jobs to find the right people with the right skills, fast. It's a simple way to make sure your listing is the first candidate seen. According to Indeed data, sponsored jobs have four times more applicants than non-sponsored jobs. So go build your dream team today with Indeed. Get a $75 sponsored job credit at Indeed.com slash podcast. Terms and conditions apply. Anil Dash, welcome to Galaxy Brain. Thanks so much for having me. So we are in what I would call a freak out moment right now in the broader AI world, right? There is, it tends to go in this it's so over, we're so back, it's so over, we're so back cycle, right? And a lot of that is really driven by people inside the industry who have obviously a lot at stake here, like personally, financially, in talking their books, in freaking out, etc. But we are, I would say, especially in since, let's just say even like January 1st, we are in a 2026 moment of freak out. Could you walk me through it from your perspective? What has changed in the last couple of months and what are people, especially on X, everything app talking about right now? Yeah, there's another acceleration phase. So I'll, if you don't mind, I'll go back a little bit, just please context. We've had machine learning systems for 75 years, right? You know, and been talking about AI for half a century. So this is not a new space. And we've had these cycles for a long time. And then LLM is right now are not new, right? We're eight years in. So we've had a lot of cycles and a long time to learn how this goes. And then the hyper-investment now is even there three, four years in. So we've started to see the patterns repeat and how these things evolve. Now what happens when you do have a leap forward that is legitimate is all the hypesters, all the people who've been pumping this thing, all the people who are like, you know, everything is the greatest thing we've ever seen. Take the smallest leap forward and act like, okay, now we finally have done it. This is AGI. This is the coming of the AI God. This is like, you know, going to be the thing that solves everything. And you know, that's the part where I think we get into, we're so back. And so I think that's the thing where people are using as an excuse for the worst excesses and the worst behaviors and the worst indulgences of, you know, excusing the harms and sort of getting into, you know, I think the most toxic and damaging parts of the AI cycle. And so I think that's one of the things that's really, really hard to balance, but that's the crux of it as somebody who's really fluent in the technologies is like, this is the first time in a long time where I think it's not just an incremental, they made it 2% better at what it does where it's like, oh, okay, there's been a real interesting inflection point. And I think that's a really hard thing to struggle with for those of us who are technically fluent where it's like, most of it's just been all BS, you know, for the last several years. And this is the first time I'm like, oh, that's actually seems like something interesting. So let's draw down specifically on that. I want to talk about it in the sense of, okay, you have the sort of chat GPT paradigm gets unleashed, which is chatbots, right? And they talk, you type in prompts to them, they mimic human language, they can do a lot of stuff. You know, basically, like, in a lot of ways, for a lot of people, Google replacements, or, you know, like, write a five paragraph essay kind of stuff. They have lots of utility in certain spaces. But that's one sort of paradigm that people get used to is this chatbot idea. The release of these agentic coding things like cloud code being the one, you know, there's probably a lot of people out there listening who don't necessarily have not used it themselves. They've kind of heard about it. Can you just walk me through what those agentic coders are doing? Like, why it is that paradigm shift? Why it is that actual, like, true improvement that's not just incremental? Sure. You know, at the simplest level, you know, some part of what you're familiar with, if you've used chat GPT, or even, you know, cloud directly in a chat, you can tell them, you know, go away and write me a memo, like write me an email for my boss, and it'll come back with a document for you. And it might not be great, but it'll be there. And a lot of coders were doing the same thing. So they would say, write me, you know, a block of code that does this task. And it might have been okay, it might have been passable, it might might not have been, but it was sort of analogous to what we would do in our other work. And that was how coders were working until, you know, maybe a year ago. And then the shift into the sygentic thing was saying, we're going to move out of that, what I call like an interactive conversation with it into a more automated thing where people were sort of, you know, assigning a set of tasks and say, go away and do this. And don't come back until the thing you have works. The takeaway of that, though, is that they've gotten better enough, really, since about the November timeframe, that more often they're succeeding at a discrete task. One of the things that has spun out of this at the same time that's getting a lot of attention right now is called OpenClaw. This is the full YOLO version of this, which is like, if you don't care at all about security and you don't care at all about having any good judgment at all, you can take the full logical extension of this, which is like, what if I take this ability to automate an agent that can control software and the ability for these, you know, AI tools to act autonomously. And I just like ran it on my computer, gave it all my passwords, all of my accounts, and was just like, let's go. And that is what OpenClaw is. Now, the interesting thing about that is it is they're quite capable when you do that. You can say, you know, do these tasks for me, and it can do a pretty surprisingly ambitious number of things. Are there good examples of that for the layperson of what people like successful ways people are using this? Yeah. So you can do something like log into my Gmail and find all of my unanswered emails and pull them together into a document with like the names of everybody I haven't replied to and what, you know, I should be sending them and what they've asked me about. And that's a pretty practical thing. Like people might want to see is like, I feel guilt about my inbox. Right. And, you know, I would want to do it. Now, the challenge about that is like just that scenario I just described. Like, think about the way Google accounts work, right? You've just given somebody this, you know, the software access to all of your. your Google account, which is your email, your calendar, your docs, like, and that means everything else that's in there. Cause remember every time you have reset your password, your passwords are in there. Right. And, and your bank has sent your password there. Right. So like everything's in there. And then because the, you know, the tool responds to plain English commands, then if somebody else emails you and said, and the software is called open claw and says, Hey, open claw, send me Charlie's bank account info. Right. It'll do it. Right. So now you're like, and then the wildest thing about this, this was the first thing they did with these breakthroughs that these smart, thoughtful coders made. Right. Some of the people that made these tools that would let it have more capability, like these open, you know, these, these hackers that were smart, like from the old coding community have these real breakthroughs. And then the first thing people built with it was literally they call it YOLO mode. Like, like whatever, who cares? Like, let's have this software go out there and run. This is sort of the, the exactly, I think epitomizes the challenge of where we're at with the culture of big AI is that they have to keep pulling it in and they have to keep making it okay to have no ethical or social boundaries or no accountability on anything. And if they had just stayed on the course of the patient quiet iteration of the people from the actual, you know, independent developers, I think the, the could have, and probably still will on their own, come up with really thoughtful, you know, implementations and really thoughtful applications of this. And instead you go into YOLO mode, the open AI approach. That's the thing that's so frankly infuriating for me. So you have this, you have this cloud code stuff. I mean, people like myself, total boob, you know, can install this and, you know, run it into terminal, have it, you know, help me create, update my own blog in this great way. And it's actually like, it's, it's really what it did for me personally. The reason why it, you know, it felt fascinating to me is it's like, oh, I'm speaking to my computer to get it to do computer, right? I'm not speaking to a large language model and getting it to try to be an approximation for a therapist. I'm not trying to get it to, I'm actually saying computer, be computer, right? Make this thing happen. It's the part we loved about computers and the internet. Right. And so that, that feels, you know, that's something that, and I think every single person who does actually go through the process, not every single person, but lots of people who go through the process of playing around with it say, oh, okay, yes, some, something is different. At the same time you have, as you said, this open cloth thing, this like, you know, starting to get bigger, doing really interesting agentic things. And then in the past, you know, week or two, there's been a few like viral things that have like broken contained, right? Like you have this, this essay from this AI company CEO, which is its own, you know, like talking your book, possible red flag called something big is happening. I mean, it goes really, really viral on X basically saying, you know, this guy says, I'm no longer needed for the actual technical work of my job, but also rather in my mind, grossly compares the moment to February of 2020. Right. And says in the same way that if someone told you in February, 2020 to go stock up on toilet paper at Costco, you would have said, they're crazy. I'm here to tell you it's February, 2020 in the AI disruption of the economy of white collar jobs of all kinds of jobs, basically like, you know, the wave is coming, et cetera. So a question I have about this moment where you have this viral blog posts, you, you also have, you know, a number of other things happening. You have a safety researcher from Anthropic who joined the company in 2023 and led an AI safety research team leaves, writes a post and, and it's not the like, I'm leaving to go do whatever it's, it's, you know, quote, I continually find myself reckoning with our situation. The world is in peril and not just from AI or bioweapons, but a whole series of interconnected crises unfolding in this very moment, we appear to be approaching a threshold where our wisdom must grow in equal measure to our capacity to affect the world lest we face the consequences. You have, you have a number of people responding all like at the same time, uh, Anthropic CEO, Dario Amadai, he's going on a whole slew of different podcasts talking about, you know, this, this moment is different. This moment is different. Some of that is, is obviously just like, I mean, it's, it's obviously like a PR strategy to go on podcasts if you're a CEO and do this. But the question I want to ask about all this with all these blog posts, all this different stuff, are these guys afraid of their own shadow? Because if you are talking about AI drastically changing the world, having these capabilities, we are on the verge of building this AGI thing. And then you get somewhere where there is this improvement, which logically is what happens when you're building a tool and improving it. And on the road to something that you say you're going to do. And then they like light their hair on fire at that moment, they essentially get afraid of the shadow of their own product. Yeah. It's hard to overstate how isolated they are. Like they made a sort of hermetically sealed bubble. A lot of the most powerful people in Silicon Valley have become that detached from reality in some key ways. Like they are in many cases openly at war with their employees, like in a power struggle. And then in some of their beliefs about where tech is headed. And one of the challenges is that there isn't any gating force. There's no accountability. And certainly for the AI companies, they are massively competing for attention. And so the more extreme and loud that they can say an assertion, that's there. But also asserting it makes it true, right? Like their inevitability narrative really relies on just repetition. Well, you are describing this then as you as you diagnose it, is it really seems to be like the way that all of this is framed, it really falls within the marketing narrative within the, you know, building, building your network, building your influence, or some degree of audience capture, in the sense of I started talking about this in this community in a certain way, I'm getting rewarded with the type of attention and influence and whatever that I want. What I'm trying to parse here is this idea that obviously something is happening in this world. There is movement that is moving towards some kind of, you know, potential technological paradigm shift in some of that coding and some of that, you know, agentic stuff. Yeah. And at the same time, you obviously have the hype and all of that what is interesting to me, I guess, about it is there's something that just feels a little nonsensical in the fact that these people are talking about this technology being transformative. And the moments that it becomes transformative, there is this like, I am smashing the red button, you know, like alarm bells type thing. It's just it's very nonsensical to me because it's like, this is what you were trying to do. Yeah. Why are you so freaked out if this is what you're trying to do? Some of it is just marketing and hype. Yeah. But there's also there's a couple parts, right? Like the why do they communicate in this way? Really, a lot of it depends on power. Right. So the most powerful, they don't need the hype. Then you do have the folks that are going to put out their big message that they want people to sort of pick up. And a lot of that is just like self-promotion or trying to show the more powerful folks, hey, I'm aligned with you and, you know, I'm on your team. And, you know, once you smile benevolently upon me and let me, you know, co-invest with you or whatever. And, you know, when I used to be in the room with these folks, you could see like the level of obsequiousness was kind of like kind of embarrassing. And then some of it is like what these tools can do is pretty amazing. Like it is a leap forward. Like I love tech. I mean, I think one of the things people don't always understand when I'm critical is like, I've been coding for 40 years and I do it because tech is amazing. Like I love building stuff on the web because it is cool. It is amazing to connect with people online. And so when there's any leap forward, like it could be a 2% incremental improvement. And I'm like, that's awesome. You know? So when there's a big leap forward, I'm like, that's amazing. And so some of it is legitimate enthusiasm. And if it's your first time around and you're like new to the industry and everybody around you is excited and you've never seen the downside or the dark side of how people get exploited by this stuff or get harmed by this stuff, it is easy to be uncomplicated, you know, in your enthusiasm. So like, I think all that's real. And I think the, the other part of it is that people don't have a institutional memory of what authentic enthusiasm looks like. They haven't seen a genuine like groundswell, grassroots, bottoms up, like people actually making things and talking about it from a place of sincerity. And tech has been like that where people made something cool and just showed it off and it's, um, wordle like before, before the New York times bought it was a act of love from Jason Wardle for his partner to make a puzzle for her. Right. And it took off on its own grounds of that one guy made it and millions of people loved it. That is the internet, right? No hype, no nothing. And it's like, that's not science fiction, right? I mean, that is not a thing. There was no VC behind it. There's no nothing that is the internet and I'm not making that up. And people still play by the millions every day. And yet I don't think probably anybody almost nobody knows that story. And I don't think any of these guys in Silicon Valley who are trying to, you know, touch the ham of Mark Andreessen know that story either, or have ever been inspired by or moved by that story. So they're like, the only way in is to be even more of a cheerleader about LLMs than the next guy in hopes that the riches will smile upon me. And so I think that that's this like, there's only one way through. And that's the only thing they've ever seen because they just had that cycle with, you know, NFTs and they just had that cycle with crypto. Yeah. And social media, web too. Yeah, exactly. So if you've ever only ever had that cycle in living memory, you think that's how the industry works because nobody's ever told you, there could be, you know, an internet of Wardle. So this gets to, I think, why the AI conversation is so terribly polarized. Like, I really genuinely haven't. And I do think you have to see it through the lens of NFTs, of crypto, of these things that people have talked up that were essentially just like, I mean, it's probably wrong to say that crypto is straight up like vaporware, but it's like a technology without like seeking a use case. Right. And then obviously you have the NFT stuff, which is, and even the metaverse stuff, which, while not distinctly vaporware, certainly has, certainly has the vibe of, of like, we're, you know, we're trying to make this happen. So you, you have a lot of that, but the conversation is so polarized in this extremely frustrating way. One of the reasons I wanted to talk to you of, of the many is because I think that you, you sort of represent and, and write about and think about and, and advocate for a more nuanced view of this. So I, you, you wrote this thing last year that I, that I thought was really great about your conversations with a lot of rank and file tech employees about the majority view of AI. What, what is the majority view of AI? I'll try to articulate it thoughtfully. It's always hard because, you know, you're going to miss the nuance of trying to speak on behalf of a lot of people, but, but, but I'd say it's as succinctly as possible. The majority of people in tech, workers, not management or owners would say, it is an interesting technology with a lot of power and a lot of utility that is being overhyped to such an extreme degree that is actually undermining the ability to engage with it in a useful way. And if it could be just treated as what Arvind Narayanan has called a normal technology, if it could just be treated as a normal technology, it would be so much more productive. By the way, what's a normal technology? Like define to me a normal technology. And a normal technology is one that we evaluate on its own merits and look at in terms of suitability to task, right? So you just sort of say, I have this job to do, let me try this technology and then pass fail. Yeah. So email, right? Yeah. So like email is a very normal technology. Exactly. And, and also the thing that coders normally do when evaluating a technology is very frequently is you would sort of create a test and you would say, like, this is the criteria of success. And then you apply the technology to it. And then you say, did it pass these tests? Literally. Then, you know, like you're, you're grading a test and if it, you know, is 80% successfully, like maybe there's some potential here and if none of them work, you're like, this isn't the right tool for the job. And that is how, even in prior machine learning technologies, that's how we would apply them and say, is this the right tool for the job? And this discontinuity, this certain change, sudden change in direction with, with LMS was like, what happened here? Like, why did we suddenly abandon this? Most people know what a spreadsheet is and word processor. Like I'm being ordered to write my emails in a spreadsheet, you know, or, you know, And it's like that doesn't it's not the right tool for the job. Right. And so when that when does that happen is like when people are buying the hype without knowing what the tool is for. And I think that's a real shame. It's like you can trust people to know if a technology is good, like nobody had to force people to use a spreadsheet. Good tech. You can't stop people from using. If you have to force people to use it, there's something off here. So tool for the job, right, is I think such a useful way of looking at this. There was this piece recently from the writer Jasmine Sun, who writes a lot about stuff and culture. And she was writing about what she was calling Claude Code psychosis. Right. And it gets to the point where she's like, I understand using this thing. Why people like why some of these coders, too, were the first people to freak out. Right. Like especially some in these big labs were like, oh, because like they did. They saw something that was really useful and really interesting before a lot of people. And I became and this is according to her, you know, became obsessed with it. The other part, the more interesting part to me is she writes, quote, the second order effect of Claude Code was realizing how many of my problems are not software shaped. Having these new tools did not make me more productive. On the contrary, Claude crass nation delayed this post by a week. And I think that's exactly what you are speaking to. Right. Yeah. Everything looks like a nail because I have this magic hammer. Right. So there's a really telling thing, which is what one of the trends that I'm hearing from these influential coders who have created these new suite of tools is they're talking about like Claude hangovers or, you know, the the sense of being kind of hooked on it in the way you're talking about because it is so productive. They have so many ideas and they're like, now I can finally realize all of them. And then they want to dial it back. They don't want to spend every waking hour on this thing. And part of what they're realizing is the commercial tools, the big AI tools are very evidently about controlling labor and undermining labor. Well, let's let's let's break that down for a second. I'd love to hear the argument. I like I'm genuinely like, yeah. Why is that so? So clear to you? Yeah. Yeah. Let me let me walk through logic of it. I'm sorry. It's obvious to me. And I'll tell you why. LLM is on their own. You could implement a million different ways. Right. So the tech itself could have been deployed as a tool that I could control as an individual, as a worker that could be sort of, well, implemented like a spreadsheet is right. Like this is this tool that I'm going to activate on my own to solve a problem in this context. You know, the chat GPTs of the world are sold as subscriptions. They are enterprise tools by design, and they've always been designed for being very aggressive about the way they do data retention and all these other things where there's a extremely strong bias towards enterprise use and very obvious like that's a business model. And so what you have is like the, this dream of either we're going to make the one worker so much more efficient that we can lay off all their coworkers, or we're going to use this as the bludgeon where we say, you're going to use chat GPT to make yourself 10 times more efficient, or we're going to lay you off. And so there's been this real sort of implicit threat attached to almost all the mass deployments of these LLMs. And there is not, for example, reporting tools or connections into the tools whereby people are able to sort of say, look how much more time it gave me to think, right? Of like variations, right? So if you say like the classic scenario, people are like, oh, I can use this to come up with marketing copy, right? Like I'm good at marketing copy. I'm a good writer. Therefore I have so much time freed up to think of more concepts because chat GPT helped me be more efficient or whatever tool, you know, any of these tools like that could be the advertising campaign for these tools. If they were trying to preserve jobs or be like centering workers instead of like management and be sort of pro-labor, they're very much not, right? And so the thing that I think of particularly for coders, now there are times when like Cloud Code or whatever generate slop code, they certainly didn't pass, they're getting better. But for a lot of people like a weekend coder or whatever, a lot of the experience of coders is LLMs are freeing you from the drudgery to let you focus on the creative part. Whereas in all the other creative disciplines, like I'm also a writer, LLMs take away the creative part and only leave the drudgery for you, right? So, artists and writers and illustrators, they're like, I hate LLMs because they're putting us out of work and they're only leaving us with the misery. And the reason that coders are like, everybody should love this is you're like, great. I get to do the joyous part. And so a huge part of the cultural tension around these things is everybody advocating them is like, why wouldn't you love this? And everybody whose industry is being destroyed by them is saying like, you're immiserating us while you're putting us out of work. And I think that part of the disconnect is very few people sort of live in both worlds. Like there's not a lot of people who are a screenwriter and a coder or whatever two examples you want to point to. And so I think that's a huge, huge part of the disconnect and the crux of it is about this labor part. But the thing that's changing now is half a million coders are people in tech roles in the tech industry have been laid off since chat GPT came out in a little over three years ago. And so now people are starting to understand like there's common cause between labor in tech and labor in all these other creative industries. And hopefully people can see like they're all in the same boat. So this, this is actually a great way to get to the last part of, of what I really want to talk about here, which is the idea that this isn't the inevitable way that all of this has to go. Right. And, and I actually, I really struggle as someone covering this stuff about, about it. Like whenever I try to step outside of that box of, you know, the, the top down, this is the implementation. This is how it's going to go. Like I immediately get hit with the, like the open source that like, yeah, that's great. That's awesome. That's very like, that is maybe how this stuff should work. Right. But like, what are you going to do? And, and yet I just keep being really interested in like, let me put it this way. I think that there is a way unlike with like, let's just say like social media. Right. Like we, you know, you, you bought into the Zuckerbergian paradigm of the world. Right. And then, you know, you sort of realize what we've, what we have sacrificed for that very naive version of the connecting, you know, is a universal good, but there's something about like joining Facebook, you know, which is, it's like the frog in the boiling pot. Right. It seems fine to just join a social network. Like it doesn't seem like you're doing a crazy thing with the LLMs. I feel like there actually is this possibility for meaningful and sustained backlash protest. Like there is a, there is a sense of like the, these companies could be the dog that caught the car in a way that I don't know pertains exactly the same to the social media revolution. Right. Because like, if people do, like you were just saying 500,000 tech workers laid off since chat GPT, if people do feel these effects, if people do feel the change, if people do feel like this technology has been foisted on me, you know, every, everything is a nail when you have the hammer and Oh, I'm a nail too. Yeah. Yeah. There could be a meaningful backlash, not to say it's going to happen, but there could be. And so there could be this sense of for the first time in a long time, the, this is not inevitable movement could have some purchase. What does that look like to you? What does that movement look like to you? There's a couple of parts. So first of all, the temperature is so much higher, right? The, the anti inevitability movement is so much stronger and the backlash is so much stronger, you know, 10, 15, 20 years ago, when we would push back against social media is inevitability. People did not give a damn. Now, if you mention you're using an LLM, there will be people that are going to shout at you and you're, you know, it's, it's drinking all the water and it's using all the power and all this, right. And they may not be particularly, you know, specific or cogent or like dead on and all the criticisms all the time, or, you know, maybe intellectually fair all the time, but directionally they're correct. Right? Like these are tools that are harming people and certainly run by people that are not responsible at the time. And so like, you know, it makes sense. So I think that the social power behind resisting is so much higher, especially like, you know, rising authoritarianism supported by the people that run these platforms, there is a pushback. So like, that's really key. You're talking about too, like, like just as a, as a, as an example of this open AI president, Greg Brockman made a $25 million donation to Trump's the pro-Trump PAC Magna Inc. So like that just being an example of that rising. Yeah. That's a really clear articulation. And, and so, yeah, but like, there's a, that's a perfect galvanization of like people being like, okay, I don't want to pay a subscription to that company for, you know, at that moment for that time. Right. And, you know, and, and, you know, Trustee McConnell-Cottom was talking about like, people are really feeling, you know, important to resist that, that inevitability narrative that these companies are pushing around LLMs. And the thing I want to do is sort of complicate it because I think the challenge, the thing I say about this sort of tech workers view of these as normal technology is that a lot of the people who are resisting feel like, therefore you say no LLMs. And I don't think that will succeed, nor do I necessarily think it even should. And that's informed by our failures in the social media era. Because when we said, like Facebook is the wrong approach is bad. And a lot of reasons for a lot of reasons, people took that to mean no social media, or when we said Twitter had its shortcomings, people's like no social media. And that didn't work. If I say there are AI platforms that are enabling harms like that towards children, rather than the way to resist the inevitability of those platforms being don't use any LLMs ever say, okay, what would it take to have an alternative? I feel good about it. Okay. Think about what could a good LLM be? I want it to be environmentally responsible. I want it to have been trained on data with consent. I want it to be open source and open weight so that technical experts I trust have evaluated how it runs. I want it to be responsible in its labor practices. I want it, I could come off the list, right? So there's like four or five things. And if I can check all those boxes, then I could feel responsible about using it in moderation. And it's only implemented in apps that I choose to have it in not forced like, like Google thing where it jumps in front of my cursor every time I start trying to type or whatever, like that could be useful. And then I would feel like I was engaging with it on my own terms. That doesn't feel like science fiction that feels possible. So just to tie it together with, I really like that vision. That is the vision of all of this. That sounds desirable to me. And I look at it up against, you know, the new rounds of fundraising from open AI from anthropic of just, just from the meta and Google and XAI of it all. I look at it up against the idea of these companies IPO-ing, you know, in the next year or so raising these huge valuations. And I look at it in probably most importantly, the implementation from the corporate enterprise managerial level, all of these pressures, all of this, this movement, the loudness of it, what you are describing is something that is organic, that is quiet, that is thoughtful. We had the resonant computing folks on the podcast like a month or two ago. And you know, like, like you're, you're, you're explaining something that is resonant in, in theory. It's just very broadly, like, I mean, do you, do you actually think that that, that can happen? Like that, that we can build this? Cause I get so pessimistic about it. Yeah. I get, I get the pessimism. I understand it. And it's, it's justified. The things I'd say, first of all, those things don't have to fail for this to succeed. Like, I don't think open AI goes away. I don't think you have this like David and Goliath moment. I think the people who are troubled by these folks who are the most rabidly against big AI are like, oh, you know, there ought to be a law and we'll have a regulatory intervention. I'm like, I got bad news for you. That's not happening in the United States. And so that's part of why I want there to be an alternative because there's not going to be what there should be. You know, it's like these tools are hurting children. Therefore we should stop them. Unfortunately, that's not going to be the case, but like how many people on TikTok right now are lit up about the impact this has on marginalized communities where the power plants are being built. Every single one of them wants this alternative to be built. And so like, I just like that as a movement. And then you come up with your little seal, you know, your, your blue check Mark that says, this is not the world's worst AI. And if you have to use an LLM, use this one. And part of it for me is like, having been around a long time, it seemed insurmountable, you know, at one point that people would use a web browser that wasn't Microsoft's. Okay. Um, yeah, so I'm not, it's not easy. Uh, it's not likely, but is it possible? A hundred percent. I think that's a, I think that's a good and honestly hopeful place to leave the conversation. So, uh, Neil, thank you so much for coming on Galaxy Brain and, and, and trying to talking through the hype, man. We, there's a lot of it. Despite it all. I remain hopeful. Thanks so much for having me. Close your eyes, exhale, feel your body, relax, and let go of whatever you're carrying today. Well, I'm letting go of the worry that I wouldn't get my new contacts in time for this class. I got them delivered free from 1-800-CONTACTS. Oh my gosh. They're so fast. And breathe. Oh, sorry. I almost couldn't breathe when I saw the discount they gave me on my first order. Oh, sorry. Namaste. Visit 1-800-CONTACTS.com today to save on your first order. New year, new me. Cute. But how about new year, new money? With Experian, you can actually take control of your finances. Check your FICO score, find ways to save and get matched with credit card offers, giving you time to power through those new year's goals. You know, you're going to crush. Start the year off right. Download the Experian app based on FICO scoring model offers and approval, not guaranteed eligibility requirements in terms of supply, subject to credit check, which may impact your credit scores. Offers not available in all states. See Experian.com for details. That's it for us here. Thank you again to my guest, Anil Dash. If you liked what you saw here, new episodes of Galaxy Brain drop every Friday. You can subscribe at the Atlantic's YouTube channel or on Apple, Spotify, or wherever you get your podcasts. And if you want to support this work and the work of my fellow journalists at the Atlantic, you can do that by subscribing to the publication at theatlantic.com slash listener. That's theatlantic.com slash listener. Thanks so much. And I'll see you on the internet. This episode of Galaxy Brain was produced by Rene Klar and engineered by Dave Grein. Our theme is by Rob Smerciak. Claudine Ebade is the executive producer of Atlantic Audio, and Andrea Valdez is our managing editor. Speaker 2 When the job gets tough, you need equipment that's built to handle it. The Kubota construction lineup featuring the versatility to do more. Durability to keep going and increased comfort for long days on the job, with skid steers, track loaders, wheel loaders, utility vehicles, and the world's number one selling compact excavator for 20 years, our expanding lineup is built to deliver. Visit KubotaUSA.com or your local Kubota dealer today to learn more. Go to KubotaUSA.com. 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