Why Opus 4.5 Just Became the Most Influential AI Model

The world changed last week. Opus 45 is the first time where I've been able to vibe code and it just keeps going without tripping over itself. It just keeps building stuff and it doesn't have errors if there are errors that fixes it. I kind of knew we were headed in this direction. Somebody on Blue Sky was like, "I don't think anyone should have any opinions on AI until they spend two hours in the opus room." And I think that's right. I know I'll go feel like him in good faith, say, human skills are gonna be relevant. One way to look at this and be like, "Okay, you can take your craft, you can evaluate the output to this and you can make sure that the people in your world are being getting good stuff faster, but also make sure it's safe and on rails." That just isn't how humans work. Man, humans want to type in the box and get a thing. And if it kind of works, they'll be like, "I did it. I don't know if society will completely reorder itself." Although in a way, it seems to be trying too. So that part's tricky. I think what's wild to me is learning how hard it is for humans to metabolize change. Everybody thinks lots of thoughts about me and themselves and their disciplines, like, I'm a front-end engineer, I'm a product manager. To see all of those categories blur and all of the things that allow people to say where their value is is frankly really overwhelming. (upbeat music) This podcast is sponsored by Google. Hey folks, I'm Amar, product and design lead at Google DeepMind. We just launched a revamped vibe coding experience in AI Studio that lets you mix and match AI capabilities to turn your ideas into reality faster than ever. Just describe your app and Gemini will automatically wire up the right models and APIs for you. And if you need a spark, hit I'm feeling lucky and we'll help you get started. Head to AI.Studio/Build to create your first app. - Oh, welcome to the show. - It's great to be here, thank you. - I am so excited to get to interview you. You, for people who don't know you, you're the co-founder of Abord, which is a AI-powered software delivery platform for businesses. But closer to my heart, you are a fantastic writer. - Thank you. - You're at a piece like when I was in college that like just, it was like, it's like VPs when I think of, when I think of that era called What is Code for Bloomberg. I would love to revisit that piece in a second. - Oh, you were in college a mere 10 years ago, oh, damn. - That's fine, you'd drink some milk and talk to me here and then that's great, that's great. - I've had you stretches now. I didn't have to do stretches before, yeah. - At least you can do the stretches, dude. - Enjoy it. - So, super excited to talk to you, but I think the thing that we were both super excited about is Cloud Code, and in particular we, wait, I'm super excited about my own product. We'll, but yeah, Cloud Code, let's talk about it. - What the hell just happened? - Yeah, the world changed last week and I think people, - People don't know yet, people, it's like, they just don't know, it changed. Can you articulate it? I have my own thesis, but what do you think it is? It's Opus 4.5 and Sonnet 4.5. Inside a Cloud Code was a step change. How would you describe it? - I will say, the most immediate thing that I noticed is for a long time we've had the ability to vibe code something in one shot that looks like a passable app. But Opus 4.5 is the first time where I've been able to vibe code and it just keeps going without tripping over itself. Like it just keeps building stuff and it doesn't have errors, if there are errors that fixes it and so like this week, I built a like fully featured iPhone reading app that it's the coolest thing. I can like take a little pictures of books I'm reading and it will do an analysis, but then I can kick off like a research agent that will go and download the source text and like do like a close reading study of it and then it'll generate a custom introduction for me and a custom reading profile based on all the stuff in my photos at. Like it's crazy, it's a fully featured app that would have taken months to build that I have no idea how it works (laughs) and that's just a new world. I'm curious what you're seeing. - Very similar, so I've been, we have a tool that, if you go to a board.com, you can use it on the web. Like you build software for businesses at the prompt and we've been trying to wrap guard rails around the chaos of vibe code because it doesn't finish things. It's the last mile's really long. It tends to lead a lot of loose ends. So we've been very, very involved in the space and stayed really connected to it. And then about two weeks ago, right? Like something changed and they sort of released their models. And I think what I would say as a log code is, I would go so far as to say, it's the first true product built on top of an LL app. There are a lot of product and I wanna believe that we're in there too and so on. But what we're all trying to do is build constraints and systems and kind of recursive methods of understanding what the output is and making it better and making the LLM actually work. The way people expect it to without all the sort of strange endings. And Cloud Code feels like they took that seriously. And in a funny way, I think it doesn't represent some giant step change in the capability of an LLM. Like it feels like, yeah, like Sonic and Opus are better, but they're not like 9,000 times better. But they added in a layer of kind of agent style, thoughtfulness to the product. So it's constantly evaluating its own outputs and then improving them, which leads to these really, really complex outcomes when it comes to writing code. And so I'm in the same boat. I have a set of benchmark projects. There's one called, there's this document, it's got a terrible, not documents. A database has a terrible name, it's called iPads. And a friend of mine asked if I could work with it like a year ago using AI. And it's a government produced database of every college, they have to fill it out. And it's like, what are their majors? And what's the gender and race breakdown at the school, and what is tuition, and so on and so forth. And it's grisly. It's Microsoft access databases and huge data dictionaries. And it's the sort of thing that literally I wouldn't have touched at an agency without hundreds of thousands of dollars to staff, a team of engineers. And really, I think it's a horrible, horrible programming to sort of take this, transform it, and put it on the web in a sort of modern way. And I mean, I just knocked it out. It wasn't easy. I still had that kind of know a lot of stuff. But it did a really great job. And it built me a nice visualization with smart search. And I had to create an AI-enhanced search tool. I've been using it to set up a pipeline to build little musical synthesizers just to see how that could work. And today I was like, hey, clone a TR-808 drum machine, and it didn't in 20 minutes, right? And it's just sort of like, now I spent a whole day as creating that pipeline, right? But that used to be like the work of a company. And so I think what's tricky-- I don't know if you have this experience. What's really tricky is you go, wow, I'm powerful. And then you realize like, no, this is everybody now. Like you feel like you've captured something. Like you got the ultimate Pokemon. But everyone's getting the same Pokemon, like shoved into the mailbox. So this is me trying to come up with an analogy that connects with you as someone who's a lot younger. [LAUGHTER] Thank you for being so relatable. Yeah, this is part of my job. [LAUGHTER] I think I totally agree. My experience-- I've been-- I actually did a whole presentation for our team this morning on what I think has changed about programming. And I would be curious-- I think you're the perfect person, actually, to talk to this about. The thing that is really interesting-- the design principle that I think made Cloud Code-- makes Cloud Code so powerful-- is that anything that you can do on your computer, Cloud Code can do. And it has a set of tools that are below the level of features. They're low-level tools. They're like files-- they're command line tools. It's bash, it's crap, it's like all this stuff. And what that allows you to do is it creates this system that is very composable and very flexible that you can build on top of and do use in ways that they couldn't necessarily predict. And what's also really important is that it means that the programs or the features of Cloud Code are actually just prompts their slash commands and sub-agents. So you can write features in English, which lets you iterate faster as a company, and also lets your users make their own features. And I think that that is a general principle that you can start to apply to any AI-based application as a product principle, which is anything in our application, anything that a user can do, AI can do. And generally, we're trying to move what used to be product functionality that is written in code into prompts that the agent uses low-level tools to accomplish the feature outcome. And that opens up all of these interesting cool new doors for software development. I agree, look, I think the patterns in this kind of programming, this kind of thinking are really, really different. I'll give you some cloud examples. But frankly, as a company that's building a tool along these lines, I think the patterns are emerging for everybody in all the LLMs. It's just that Cloud Code just really bundled them up very, very efficiently. And it kind of hit its core audience of engineers, which is them, just like, right, it's just a slap across the face, because they literally were like, here it is. Here's the future. It's going to look like this. And we all went, yeah, all right, man. You got it. Yes, yes, yes, Mr. Claude. There's a few patterns, right? So, hey, yeah, everything you're saying, you're bundling stuff up as sentences. There's another aspect of it, and it integrates with the existing system. So it's not like, it's not this world apart. And actually what I found over the last week is where I normally would go to a command line and start typing. I start typing in English. And forgetting I haven't gone in to Claude, right? I'm just, it's so immediate because it's so much better at building and orchestrating. And you know what, it's funny. I'll give you an example. I wanted to deploy something I built that weird database I was talking about earlier. And so I went to fly.io, which is a very fast deployment environment, and I was like, you know, 'cause I bet it'll be able to coordinate well here. And then I just was like, wait a minute. I have this random server just like sit in somewhere that I use for scratch projects. Can you just SSH into that and just deploy this thing for me? And I was like, yeah, no problem. And it just like jumped onto the box. It's like, looked around. I was like, yeah, it's a new Ubuntu server. Yeah, let me update your engine X. Ooh, you need to get the certificate installed here. Let's go ahead and do that. And 10 minutes later. And then the killer was I was at Thanksgiving. And my friend's dad was like, boy, I really need to make a searchable index of this one politician's newsletter for OPPO research. And I was like, man, that's something. He's like, yeah, I've been cutting and pasting into Google sheets. And I'm like, is it all available on the web? And he's like, sure is. I open up Cloud Code on my phone. And literally between Turkey and dessert, I built and shipped it. It was SQLite on the back end. It works just fine. He's going to do his OPPO research. Don't worry, he's on the right side. And like, and so like I shipped a pretty complicated search based full text search. Like I know that whole architecture really well. So it was really easy to instruct it. But off we go. And it also is good with dealing kind of like, I didn't have to use all the new custom fancy stuff. I could just use an old server that was sitting around because it knows. And so there's all of that going on. And I think that as I've been working with it, what I'm finding is you've got to think, not just like in terms of solving the problem, but in terms of like a one level of abstraction up. Like I built a little, I had it build a little musical synthesizer for me that emulated like a moog synth. It's something I know a reasonable amount about. And it did like an okay job and had a lot of caveats. And the remaining work on it would be hard and I didn't do it. But then I was like, okay, one level up. You need some more information about digital signal processing. So I'm going to go spider some books that are available free online and I'm going to put them into a database. Whenever you have a question, search this little tiny SQLite database and refer to it. So then I give it a reference source. And then I was like, wait a minute, you keep writing code and cloud, you have to calm down because your code's okay, but it's not that great. I want you to go find all the open source libraries that are really good about digital signal processing, which is really edgeKC. And I want you to make a list of them and I want you to only build based on those things. You should adapt and create a library and then you should implement based on that library. And as like five or six things, five or six things at that level of abstraction unfolded, I'm now able to say, hey, make me a synth that's like this and come back 20 minutes later. And that is a lot. Actually, it's a little emotional and confusing to process after 200 years as a software person. But if you work at that level, and I think that's the skill that's going to be emerging. - Yeah, I agree. I want to stop you there at the, like this sort of emotional level of 200 years of software engineer. And I think that there's probably, there's just a lot of people who are professional software engineers who love the craft of code and who maybe are pretty skeptical of AI 'cause they're like, well, I can't write the well-crafted code that I can write, you know, it does all these things. It does all these things that are, you know, the code is not efficient and it's maybe not as dry as it needs to be. It does like stuff, right? And also, if someone like you uses it, you can like move to this level of abstraction where to some degree, that code doesn't matter or it doesn't matter as much as it used to. Like how do you, how do you square that sort of like craftsman mindset about code with what is now possible? - Damn, man, I don't know. I don't know this week. I mean, I think two weeks ago, I would have been able to be like, "Wah, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go "Where are you going, where are you going, where are you going, where are you going?" Roughly the same, it just feels like there, but there's also this element of like one of the things we haven't talked about yet is you can instruct it to get better. You can be like, "Hey, if you were Claude, if you were, I was like, if you're a really good engineer at AnthropA, take a look at this code base and tell me how to make it more efficient." And it's like, "Well, I would do these things and get this stuff out of this file and put it over here and make this more searchable and let's make a command over here and let me write you some code." And so it's self-referential, which means it can accelerate, and so what I'm getting at is I know how long I feel like in a good faith say, "Hey, calm down and take it as it comes. Humans or human skills are going to be relevant. I don't know if this is going to be a really good time for everybody because you've got 600,000 jobs in like Accenture alone. There's like 50 million devs in the world. There's a glut case to be made, which is, "Hey, everybody can clean up their roadmap, and it's a real great time for engineering to capture the value here and bring that acceleration to the organizations that they service, and everybody can have their thing." And that is really exciting and motivating, and I think that would be one way to look at this and be like, "Hey, you can take your craft, you can evaluate the output to this, and you can make sure that the people in your world are being getting good stuff faster." But also make sure it's safe and on rails. That just isn't how humans work. Humans want to type in the box and get a thing, and if it kind of works, they'll be like, "I did it, just like you with your app or me with my apps. They might be crap. You might be looking at this, and you might have app glaze all over it, just like we see with images and text, but you can't see it yet because it's so shocking, except that it's software, and it's not like, there's no API glaze. It pulls from the database where it doesn't. So it's just this very confusing moment where it's doing really practical, really difficult things that used to be really expensive, and all I can tell people to do is like, somebody on Blue Sky, I don't know who was, just was like, which Blue Sky doesn't love this stuff, was like, I don't think anyone should have any opinions on AI until they spend two hours in the opus room. And I think that's right. Just give it two hours and see where you get, and then you can be as grumpy as you want, but you gotta give it a go. I agree. I think, and I would love to get to some of the social implications, but I'm mostly interested at first, because I think the only way to, or I think the best way to understand the larger implications is to understand the implications on yourself. Like, how is it changing how you process the world and how you think about yourself? And so I'm curious about that for you. You know, it's funny. I'm building a AI company with a wonderful business partner I've worked with forever. I'm looking out, we have a nice office, and we have a great team, and we have clients, and we work with them. And we're doing what I just described. We are moving their roadmap along, and we're bringing them tools much more cheaply and much more quickly than we used to be able to, and I think it'll get faster, right? Like, we want to, we want to drive that value out. And so in some way, things are pretty normal in that I come to work on the train every day. And in some ways, they're not in that there was so much friction built in for good reasons into the software development process, and the software development process is social, you know, like engineers say know a lot, and they say no for good reason, and I used to train them to say no, because clients would ask for things, and it would blow up the scope. And then the whole project wouldn't ship, and then they'd call me on a Saturday, and yell at me, and I didn't want that to happen. And so I'd be like, we've got to say no, I'm front, and my co-founder has a wonderful maximum, which is there's no bad news 90 days out if you see something failing, and you tell somebody, hey, like, I think we're going to have a problem, I'm not going to be able to build your thing, but it's three months ahead, and you say, let's work together to find a solution, and people tend to be very accommodating and understanding. It's only like three days before when you're like, we're going to miss the deadline that they freak out, and so my whole life has been architected around the fact that everything I do is exhausting takes time and involves some of the most difficult people who have ever existed on the face of the earth, we usually hate me and each other. Okay, and like, that is my day to day, and I'm pretty good at it, and everybody thinks lots of thoughts about me and themselves and their disciplines, and people are very, very anchored to their disciplines, right? Like, I'm a front end engineer, I'm a full stack engineer, I'm a designer, I'm a product manager. And to see all of those categories blur, and all of those rules change, and all of the things that allow people to say where their value is. is frankly really overwhelming, and I don't, I don't want to devalue that emotional response because I've been kind of coming in and being like, hey, let's all do this together and let's move forward, but boy, I don't know about you, but there are elements of this that are just a frickin smack across the face. You probably lose so much time in the gaps between tools, you design in one place, you write and manage content in another, and then you publish somewhere else. Every jump is a chance for work or context to get lost, or for something to go wrong. Framer is different, Framer already built the fastest way to publish beautiful production ready websites, and it's now redefining how to design for the web. 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I've had moments of that both on the writing side and on the coding side, but I think that we're so in the center of just figuring out, "Okay, what do we do now?" It has quickly shifted to, "There's so much to do." I think I'm familiar with the emotional experience. Well, you chose to jump in, right? You're like, "I'm going to build infrastructure and community in order to address this change." We built a lovely office. You should come visit. Literally, because we know that New York City is not ready for AI. And we're like, "Okay, let's at least have a place where people can like, and we've been having now, for profits in, and lots of folks who are going to get ignored, so that we can talk about this." I think that part feels really good. I think it's just like, "It's a lot of change. We're coming on. We've got GLP's pandemic, and now that's -- (laughs) Writing is funny for me, too, because I'm like, "I actually see, the writing is because it doesn't write for me. I kind of don't get it to write for me. It can't be me. I just am what I am as a writer." But I see a lot of people who aren't writers. And my God, it's good for them. It gives them access to a world and to kind of entrate into a more formal style of communication that they didn't have before. And so, to me, writing is supposed to empower. And if the robot helps you, that's good. If the robot thinks for you, that's bad, so. Yeah. I think I've been trying to process, "Okay, what are those moments where I have that existential freak out? What is that like?" Because I had that a few times during this process, and each time I've once I got over it felt like, "Okay, there was something there that I missed, and I'm trying to update my intuition or my analogies for, like, so I can understand those experiences better." And there's that moment where the present sort of like collapses into the past and everything that you used to know looks really old and you're like, "What's next?" And the intuitive experience that I think matches to this most closely is, before we had really good C-travel, we used to think that if you went into the ocean, there would be like an edge that everything would fall off. There's an edge of the world. And that's our intuitive notion in a lot of ways of what happens when you get to the horizon. And what we found when we got to the horizon is that there's more horizons. In my experience, I think that that maps pretty well onto my experience with AI is like, each time I encounter this new thing, I'm like, "Oh, my God, I'm at the edge of the world." It's a cliff, and it's just going to drop off. And then each time I step over the horizon, and I'm like, "Wow, there's this whole new territory," which is not to say that there are no bad effects, and there's not complicated social issues to work out. But it is to say that I've learned to catch that edge of the world intuition, and I've tried to update it with, "There's probably not an edge. There's just a new horizon." That's a good way to look at it. I agree with that. I think for me, I don't think human beings are going to change. I don't know if society will completely reorder itself, although in a way, it seems to be trying to. But I think what's wild to me is learning how hard it is for humans to metabolize change. For me, the moment, the one that blew my mind, the last time I felt this way, just like exactly like this, was, "My doctor put me on Munjaro very early. I needed it." What's Munjaro? It's like a Zen pick. It's a G.O.P.1, okay? So suddenly, after a lifetime of not being able to lose weight, I lost like 70 pounds in a hurry. I was very dangerously big. I'm still pretty big, but my health changed. It was really after a lifetime of being told, "This is how this works. This is the only way it works. You can only do surgery." There is willpower and so on. So there's all these rules in this whole social system and things that I heard from doctors. It was one day they went, "Bh, bh, bh," and it was really confusing. It was real, "I'm an adult man," and it was really confusing to go from, "This is the system of the world. This is what weight is. This is what obesity is." And these are the only ways that things can change. And then to hear the next day of it, actually, it kind of wasn't medical condition. Whoops. And then knowing that this would push through the world and this would change the way that we talk about our bodies completely. And it did. I knew in that moment, "Oh, we're not going to put this back in the box. This is going to be very different. People are going to have very strong opinions about it. Oprah is going to do a special, and here we go." And I feel that way about this, not that we can't process the change, but just that a year or two, which is how long it's going to take for the idea that you can just have code by typing in a box and it's pretty advanced and it does things like ship apps, is nowhere near enough time to process that. Like, it's just nowhere near, and it's actually going to look like that horizon. It might take a couple years for people to figure out that they can have any software they want anytime. I use the concept a lot. I call it latent software, like PDFs that describe procurement forms or Google spreadsheets that are floating around. Like, my company aboard is all about taking latent software and making it real and getting into people's hands. And so, we've been trying to coach people along, and they're very confused. And now you're about to see, like, you know that open AI is going to build their on. And you know that it co-pilot's going to get smarter. And you know that there's going to be super mobile ads, if not this year, the next year, about how you can have anything you ever wanted. And we just rebuilt the whole society over the last 30 years around software, right? Software's eating the world was this whole idea. And now it's eating itself. And so, like, I do, look, you're right. Like, are we going to, are we going to be okay as a species? Yeah, about as okay as we ever are. There still be jobs. Yes. Right? Like, I don't, I'm not actually a pessimist, but I am, after the pandemic and GOP ones and Trump and everything, I'm just like very nervous about the human ability to tolerate change. And we've created the ultimate change engine that sits in the middle of our global economy, and spews out change, like, at an unbelievable rate. And we, we just created the number one change accelerator possible, which is move software much, much faster. And so, I don't think we're going to see, it's not going to be familiar. Parts of it will be very familiar, but I think parts will be very, very weird. And it's going to be really, really strange to watch. I love the GOP one example. And it's interesting that you listed GOP ones with Trump in the pandemic, but I assume your, which, you know, in my world, those are two pretty negative things, but GOP ones, I assume your, I'm big positive, you have a positive experience with them. So it's sort of interesting. It's hard. Man, I, I was in client services for 20 years, it's hard. I still am. It's, I have a really good product that can really help people. I have an organization that can really help people. I see Claude code showing up, and I'm showing it to people in my world, because similar to you, I'm like, whoa, and they're like, well, hold on a minute. And I'm like, no, I, and it's not me saying I want you to use this. I literally just want to say it was like this when I was writing. I just want to show you so that you can figure out what to do next. What I have found over and over in the course of my life is that merely by showing people they tend to panic. They don't want this change. And they say they do. They want the output. They want the value. Everybody wants to be an app developer, but what they want is it to run the way it used to. I don't know if you've noticed this, but every product manager you know is now building their own app, and every engineer is building their own app without product managers, and the product managers are building without engineers and the designers are trying to figure out how to ship. And they're all really happy to get out, get everybody out of their world, right? And they're pretty sure they're going to be able to capture the value of the revolution. And they wanted to follow the rules that used to be there, but it won't. And so you can be, I like, I don't know what we are. Are we all pipeline builders? Are we all coders now? Are we all now app builders? And like, everybody's having experience you and I are having who is deep in on this, but we're about to find that everything we created is probably more disposable and less exciting than we thought it was like two weeks from now. And so I am puzzling that I think it's, I think this is going to be a rough one deep down an exciting one with an enormous amount of good things, and I can't, I'm so excited for everybody to have all the software they ever wanted, because that's always been my dream. But now that it's here, I'm a little scared. Isn't that interesting? Like, I've been thinking about that too a little bit is if I take a step back and like, reround like seven years or 10 years, and I said, there's just going to be a thing where you type into it and it just makes whatever you want. Yeah, I would have been like, that's great. That's definitely not scary. Yeah, they've been promising this, they have been promising this for 70 years. And then it just happened and then you're like, like, it makes me a question if anything could happen that would be an unalloyed good. No, that's been the lesson of the last like 15 years. No, he's the answer and then I don't know, like, that's also the lesson of adulthood. And it's also the lesson of working with people when you work with people, their best qualities are always their worst qualities, you know, I'm good at thinking big thoughts, but often terrible at delivery. So you have to pair me with somebody who's good at delivery. Yeah, you know, because I get distracted. The, you know, it's funny that I'm tangential to that. The promise of software, if you go back to like the Xerox Park days, even before list programming, language and so on, is that we would have sets of composable objects that could interact and that an average human being would be able to learn the system and build whatever they wanted. Yeah, that was the whole point of like Allen Kay and the Dyna book and the 70s. If you don't know what this is, like, it's very legible. It's essentially like a laptop that kids can use to build any software they want proposed in the 70s at Xerox Park. Go look at the Wikipedia page. It's, it's kind of what we thought and that we thought that was going to be the iPhone, right? We thought that was in particular the iPad to the point that like Steve Jobs and Allen Kay were kind of like talking about that in the, as the iPhone was being rolled out, like, hey, I think we're getting closer. The idea was you'd manipulate code in ever more abstract ways. And what happened is LLM's computers continued to suck and suck and suck and be horrible and never work. And our solution was actually to simulate humans so that they could do it for you rather than make the computer really, really usable or figure out how to make really, really robust code. And there's good reasons for that, but I don't want to go into the right now, but like that people been trying for decades. And so suddenly we have it. We have the fantasy of the 70s. I could sit, I can train anybody, I think at this point, to think algorithmically and structurally enough about applications, you know, and there's going to be a lot of retooling around how we educate people about what software does. But I think in about two weeks you can start to build really, really meaningful stuff. And I think in about two years you can probably build just about anything. And that that used to be the work of 20 years. That is great. And it is great. I don't want to like freak out too much. I just spent all the Thanksgiving weekends were like just ended and I just spent too much time on the computer, I think. But I want to I want to stick there because I love this. That's the story of adulthood because the you're absolutely right. And it that is my problem with a section of the AI discourse that is I would say more the mainstream section, which is has this hidden underlying assumption that anything that could have negative effects is bad. And so and is looking for the only those more or less as opposed to like a little bit more like in adulthood, you're like, there's some really good stuff here and there's some problems here and it's sort of this like, you know, wonderful and terrifying mix of things and our job is to acknowledge the good stuff and deal with the bad stuff as best as best we can. And I think that's what's that's what's difficult to access when you're at the edge of the world, you know, is like, oh, OK, I know exactly what you're talking about here, I see it differently. So you've got a variety of discourses. So let's let's take one, which is the. And the one you're talking about is like very left adjacent very much shows up on blue sky, right. In some ways, that's kind of my home base. I guess my family, the way I was raised. You've got one group that is like AGI is coming get ready. The computer is God. OK, and so like we've all kind of learned to make our piece with them. They don't live here in New York City. We're just going to like, they seem good. It's a lot of guys. A lot of polyamory and good for them. I wish they were yoga, you know, and they also really like they've also kind of all shut up about AGI because there's so much money to be made, like, you know, right because he wants to be Steve Jobs, but he's Steve Balmer. He just kind of got the wrong Steve and and it's just like, here we go. OK, commerce capitalism is a hot take. Am I wrong? Tell me if I'm wrong. I would love for you to unpack that. I think that's I think it's a great. It's a great line. Oh, do I even need to he's a really, really good salesman. He's a really good deal guy. He told us we were headed towards A.I. Jesus. And now we're getting shopping. Right. Like, he's he's a commerce guy. I don't actually I think he's good at that. You know, I think inthropic. It's funny if you compare the two companies like opening eyes very much Microsoft, like, whatever you want, whatever you want. We're going to sell this to you. And you're going to have it. God, yeah, let me give you more. And and anthropic is Google. Like, and it's actually funny because look where they're buying their chips. Like, like, anthropic is literally buying Google TPUs. Like, they're I thought you're going to say anthropic is Apple. No, nobody's Apple because nobody's really Claude code is great, but it has nothing to do with human beings has to do with it. It's still for engineers. You can't put anyone you can't put a civilian in front of that interface. It makes no sense. That's true. You just can't now. Could they get there? Maybe I just don't think they even want to. I think they want to just accelerate accelerate accelerate engineering and let everybody go run off. And then they'll figure out how to productize along the way. Whereas, like, I think, open AI wants to make a play for the whole Shabang. They want to be the operating system. And the Apple in the middle, the people, like, what's it going to look the thing about Apple is it made the computer disappear. So who's going to make the LLM disappear? Right. And just sort of align it with what people want to do today. And I don't know for even there yet with this technology. I don't think so either. Oh, so wait, so that's that's group one. Okay, we got group one. And then here is my I'll actually give some advice, which is Silicon Valley in particular dropped this absolutely bizarre thing told everybody it would solve every possible social ill and didn't really come with a plan. And there were real harms that emerged and people panic. And the harm frameworks weren't clear. And I think what we got to do, because I'm in there too, man, I love this stuff. I use it every day. And then I go on blue sky where like 80% of my feed is people saying how much they hate everything that I'm touching all day long. And I get it. I get it because they also hated the tech industry. I think you got to just like let them burn it out. There will be people who just hate this shit for the rest of their life. And what you'll find because I'll tell you here's what's wild. And this is actually as someone who's very much kind of on their I feel I'm on their side. I got my kind of progressive type literary types from my you know, he used to be an editor at Harper's magazine, right? So like there's a whole world there for me where those people want nothing to do with this. They want their pros untouched by a robot. And they want a certain world and a certain vision of the world to persevere. And this is all noise and distraction from that just like everything is just like the tech industry is just like the web is like blogging was. And they're just like please let me get back to my purity and please get out of my hair and OK, like that's what they want. Then I think there's an but then there's this very tricky thing going on. There's a lot of people were like this is just an unalloyed evil and we have to reject it. And at the same time I'm sitting here in my nice office in New York City, but I'm hearing from and working with children's health charities and scientists and real dogoaters and climate types who are like this can accelerate our road map. And we want to do it. We want to use these tools to achieve our mission and their mission is unalloyed what I believe to be positive in the world. They see the value they're often coming to it like as scientists they see the risks and they're like let's please use it in order to get that done. And they are not software is not the star of the show for them their work is their community their donors and they're like what can we do to aggregate the data or deploy the platform or manage the content or do this stuff. In such a way that we can do more of the other thing we want to do which is we believe an unalloyed good for the world and they're super excited motivated. And so what I see when you're talking about that stuff there's actually a strange fork there's a group of people who are like I believe that I have a really good ethical model for what humans need and I believe we have to reject this our right. And then there's another group that is like I believe that and it's my day to day job. And group A is like keep this out of everything and group B is like I can't wait to use more of this and it's very very confusing and I think that tension is going to just keep rising. And then the same time there are people who are like I'm a professor I teach research methods I don't want this near my students I need their brains to work. And I get that I actually think that's right like good okay draw that line make them figure it out they're going to go use it anyway they know that. But like if you want to put them in a box for a minute so that they actually learn the history of how to think and what to do. And you feel that that's important as an educator I'm not going to second guess you I respect that. So I think it's trying to find a balance and all this but ultimately the balance is like you're there with that prompt and it does something for you that's really useful. And kind of knowing what's good and what's bad about it and then going on with your life because if you even try to engage with any of the discourse around this technology you're just in hell. Which I mean I'm glad I didn't start a business totally focused on that problem. This is why I stay off a blue sky I can't imagine what I can imagine being you. I get a funny hall pass with this stuff because I'm an old and you know just like I just I still get yelled out on a regular basis but yesterday I was just like Simon Wilson who I'm guessing many of your listeners. No, it's just like wow he's sort of stirred the hornet's nest by talking about I was changing coding and I just did a like he's right you should listen. Post and you know like half the people what what happens is everybody comes out and they're like yep, yep. And then the other half are like no there's this one time and it's death and it's and let him fight man let him fight your mentions. I think this is actually a very typical. Basically reaction to a paradigm shift and to some degree. People who have who are like. Know how they do things and want to keep doing it that way are just going to keep doing it and it's the same thing you also got people coming in from the west coast telling you how it must be done forever more. Yeah and that's it feels real bad like and they're and they're just dismiss your concerns right we're used to it we're tech nerds and we're used to we're used to nerds just kind of like stumbling in. Nerds never actually fully acknowledge how much power they have in a room and so they're like whoa why is everybody so obsessed is really cool technology and then. You know it's like well because I was going to make my living as an illustrator and I was going to send my children to like you know we were going to go on vacation once and they're like hold whatever you be I and like that that whole thing that's how that comes across. It's just this 10 year on the west coast and it is pretty hard for people I think to be told over and over how they're it's okay that they're being devalued. Without being celebrated in any way and and so you end up with stuff like anthropic having to pay 1.5 billion dollars to publishers right because like of all that stuff you know it's just like these. They feel vulnerable and then they feel attacked and then they're going to use what power they have and one of the powers they have is to just complain. And I don't know I think you got that we have to own that because we got to keep all the money. This is the leaders of our companies. What I want to understand what I want to understand like I love the they feel vulnerable and if you feel vulnerable and something new comes along it's like it's an it's an obvious immediate reaction to be like this is bad I don't I don't like this. But doesn't help that they all went to the White House and cum by yad would Donald Trump including Jensen Huang I mean it doesn't like help the vulnerable people feel less vulnerable. Let's just put that out there anyway go on that lost my mom which is for real. But what are you doing in league with Satan? You're you're you're replaying my Thanksgiving conversations. No, my mom is much much she's very proud. She should be very proud. She wants me to be careful. You better be careful with the league. I think but let's let's annoy ourselves you know in between worlds type people where we like the tech stuff and then we're also care a lot about writing in the humanities. And so ideally because we're amazing New York tech people we can cut we cannot kind of be the bridge that's missing between these two camps. And what I want to understand let's say we're trying to literally we you and I can do an event have a nice space we can we can bring them all here. I would love that that would be amazing. We're going to do that we're going to do we're going to do an event where humanities people can come yell at us. I didn't sign up. We're going to bring in the angriest overpaid professors who most expensive schools in America to tell us how bad we are. Let's just let's take the balance perspective for a second and say we want to examine we want to examine the the arguments of the people of the people on the left who are loudest about this being bad. And like what are the what are what do you think are the actual real bad things that have happened or are happening or will happen that a reasonable person who loves this technology should care about. That's a very good question. Let me think for a second for running my mouth. Because I think look, there are a lot of stories and narratives about specific harms. You see them in the paper. And you know, it'll be a chat GPT encouraging suicide in teams. And I think there's an element. I have a I have a trick your reaction to that because as a technologist. I've watched and I'm 51 right so I've watched like two or three generations of internet technology and these harms just spill out at scale. And it's really not stopping the harms is not always possible. You have a new technology. You see ways and and I think what happens is you see these works they get. They get a narrative of their own importance in the world because they're getting constant positive feedback. The money's pouring in people are saying my God, you know, my this really helped my daughter, this really helped my son. Because we're using this in all sorts of exciting scientific ways. And then they're shocked when something bad happens right because there's so much good pouring in and it's coming with so much money and they're shocked. And then they do like a full court press and then you end up in this like bizarre cycle. Where you know, it always ends up with like somebody getting really into MMA as like a CEO right just sort of like no but I really think that that's like them asserted they they they're so they feel so attacked and they feel so vulnerable. Because people keep telling them that they're kind of evil that they're like I'm going to become a fucking cage fighter and that's going to show them. And you know it's like it's kite surfing is like the gateway drug to that and like it's just like a whole thing that happens. So you've got this whole like cultural dynamic playing out inside of giant tech orgs as the money pours in and it's like a whole thing. And then you've got the press desperately seeking for very specific harms to get a story that can turn into a narrative that can be a little bit broader. And you smash those two things together and it's pretty hideous and the only way that you resolve that is through regulation and oversight. But our society is at least a little bit collapsing and it just doesn't seem interested in that. And so so now what what would be a way to do with this first first of all I don't want to what would be a thing to do here first of all I don't want to put elements back in the box. I would say that when we're talking about harms not specific harms the lack of provenance is bad I would like to know what goes into my meat. I want to I want to I want some nutritional guidelines as to what's in my anthropic LLM and what it's using and where that data came from. I don't want to be surprised by huge copyright cases I shouldn't be I should know what I'm using. I know that Google is the web roughly and Google doesn't go into secret parts of the web and it honors robots.txt. That is a contract to Google me with the web and when it doesn't honor it it's really bad and in fact there have been technologies where Google kind of like tried to sidestep the open web and people got really upset like AMP pages and things like that. Oh you and I are you drinking a spin drift tropical lemonade. I love it looks like I am too. Great minds. Spin drift. The brand of New York liberal tech nerds. God is so bad. It's terrible plays to be in technology next week. So anyway coming back to it right like. What is the harm that's been done. We won't know the real harm not the specific harm but the broad I don't see it as harm I just see it as change what kind of society do we want to have to deal with the kind of change that is coming. A 50 million person underpinning of the entire global economy the tech industry. You've got giant consulting firms you've got console tech integration firms and software companies their core product has been radically devalued. What do we think about that who gets to talk about that like who is going to the AI folks are going to be like it's great it's best thing ever happened everybody gets their software I'm going to say that because I'm building a product along those lines but like if we're going to have this level of change it almost feels like you're not even what I think is going to shock people is how. How people see it coming but then don't really plan for it like everybody and that's what actually panics me a little bit then I like. Because people are like well you're still going to need engineers for this and you're still everybody is like well but when they see this new technology and I think we have to start internalizing. And actually horizons aside this will change a lot of the ways the people do things and it might change the way they make money and it may change what their lives are like so what's that going to look like. And ironically I had Claude make me a prediction model for the future of the consulting industry and right me little stories. What's that what'd you get what did it say dude they were really sad I was like I know because I literally was like okay you know what Paul you get a little cynical just say mild bearish mild bearish okay and it was like. Rahul thought that he had made a good choice by going to computers. Like one after the other it was like how to draw a sank you chart I can share it with you can share it like it's I published it as an artifact here let me just give it to you let me let me show you this thing please hold on because I want you to I want you to see it. One sec there you see that yep I do okay so this is I didn't give it this title. And in fact I tried to really hedge I was like hey looks like I might really change the consulting industry and I wanted to make a sank you chart and tell me. It's one of these guys okay so it's like the dollar chart yeah yeah stuff comes in on the left stump and it gets turned into work on the right so like financial services clients you know feed in and then and they make this much money off of consulting so right now we're looking at the light giant consulting firm. And it does audit insurance and consulting and tax and legal let me zoom in a little bit and just zoomed in on you here we go. Okay so mostly like and like I said I said mild bearish case it does seem like this could really affect these industries just show me kind of what what might happen if AI was going it's kind of ironic to ask quad. And so I was like let's look at McKinsey everybody loves McKinsey every favorite company. So $16 billion in revenue 45k employees headquarters New York City and in 2024 there there revenues about 16 billion now I didn't have a due deep research it was just very handways I'm guessing all this is kind of wrong let's be clear like it's not. But it says that by 2035 McKinsey's revenues if it loses digital services are going to get down to 4 billion. And so you can see that here if we switch to 4 billion the whole chart shrinks and we go you know let's go back to right now we're making our money through corporate strategy operations and so on. So I had it right employee stories for each company and so I'll answer everything right. Oh yeah everything Stanford undergrad Harvard MBA McKinsey associate 27 and she was on the partner track billing 800 an hour to tell fortune 500 CEOs what they already suspected but needed external validation and thought I gotta say Claude just decided to burn the shit out of McKinsey like it just again like I'm not I'm not grinding an axe here I was just like you know just write little stories about what's up. The dirty secret of strategy consulting was that the frameworks weren't magic they were structured thinking applied to ambiguous problems and structured thinking turned out to be exactly what AI was good at by 2027 a CEO could upload their companies data describe their strategic question and get a McKinsey quality analysis in an hour complete with market sizing competitive dynamics and three options with trade offs. It wasn't as polished didn't come with the McKinsey name but it was 90 for 5% is good at 1% of the price. McKinsey tried to go out market we don't sell analysis we sell judgment the partner said we sell access relationships implementation support but implementation was getting automated to relationships only mattered if you had something valuable to offer. Alex made partner in 2029 just as the firm started its long contract she was one of the last by 2032 McKinsey was a quarter of its former size serving only the largest clients who needed the brand for board cover again damn Claude. She left for a client chief strategy officer of mid cap industrial company less prestigious more stable she actually got to see her decisions play out which was novel. Oh my god sometimes she missed the intellectual intensity the feeling of being the smartest people in the room then she remembered the smartest thing in every room now was the computer. Incredible incredibly. I'll share this with you so you can share it with your listeners but it is it's a clog code artifact that I built yesterday for fun and I shared it with somebody works at one of the firms they're like I got the numbers a little bit wrong and then they were just really quiet for a minute and they went interesting. But yeah Accenture Rahul had spent 15 years armies got smaller they disappeared and then at the end he took a buyout at 45 started a small consultancy helping mid market companies with the human side of AI adoption change management the squishy stuff the AI couldn't do well it's a living some weeks he almost believes he's adding value. Wild bearish anyway you know I think is it a little ridiculous that I'm using AI to explore this particular part of the world sure is it or do I do I buy this no because I actually I do your horizon thing is real nobody knows what's on the other side. Right this is a the mild bearish case is is that an economic contraction won't have a sudden flowering of new opportunity and the people won't figure out what to do next and they'll just be captured in this kind of like shrinking world robots do more. For the rest of their lives and that's not actually how humans and societies work click. But I do think it is a change at that level of magnitude that we're going to have to react to I agree I love I love that I think that's so interesting and I think it's actually a good. Example of why language models are so powerful and what makes them sort of special and and in that is an interesting example of why I think consulting firms oddly are going to still be valuable and important. Let's bring that in let's hear what you got great. So the the thing that it seems to have picked up on in its mild bear case is that you can get the analysis and the judgment for you know 1% of the cost. And obviously like this the thing is like oh it's not buying analysis judgment or whatever but there's something I want to stick with the like analysis in judgment for 1% of the cost because like I've done this to I have. Put all of our company financials into cloud and had it right our investor update and it did a fucking phenomenal job. Yeah so good anything kind of bureaucratic is just magical yeah and I've also done a lot of strategy stuff with it and. I think the I think you get one way to you can break up human thought or just. Ways of solving problems into two broad categories. In one category there's a right answer and it's extremely rare but there's only one it's a needle in a haystack which is what traditional programming is actually quite good at. It's math it's logic is all that kind of stuff can be example like this kind of like excel spreadsheet. Exactly you know how profitable were we were this this corner is like a you know there's a set of rules that you can apply and there's a there's a one right answer because you have very precise definitions of what right is make me a pie chart of what we're selling exactly. And on the on the other end is and and the literary analogy is the Borges story like the library of Babel where it's like every book is there but there's there's infinitely many books between where you are and where you want to get to and they're all nonsense so you you're just always a nonsense basically unless you've artificially constrained the search space. The other the other you know I don't know branch of human daughter or way way to think about the way the world is is. Instead of this live this infinite library where you're you're sitting in this sea of nonsense but you know that if you go get through enough nonsense you'll get to the right answer and there is a right answer because there's only so many you know pieces of hay between you and the answer you're going to get to the needle in the haystack on the other end is a library where every single book is meaningful and has a story. There are infinitely many books between where you are and where you want to be it's not count it's not countably infinite it's just it's just there's you're just sort of the in this enchanted forest of stories that you can that you can go read and each of them has has a plausible sounding answer. And you have to use your own human intuition or judgment and and feedback from the world to like move your way to like generally the right area but there's no right answer. And when we're thinking about a question like when we're thinking about a question like what's going to happen to consulting businesses or what strategy could consulting businesses take or you know what's the mile bear case. I think we're much more likely to be especially if we're looking at a cloud answer in the regime of there's infinitely many meaningful stories and we're looking at one of them but sort of treating it like it like it's the this other one where it's like there there's a right answer and cloud just found the right answer. Because if you change your prompt slightly you're going to you could write you a great story about why consulting businesses are going to do really really well. It's a it was a mirror of my anxiety at the moment but you're absolutely right like I'm one literally five minutes away and if it hadn't told me that I was running out of opus credits I probably would have done it. Which I wasn't by the way a little product problem there in case the people from Anthropical I had 20% left and it's like hey we're almost done here and I'm like really because I have a problem but it's not that profound so anyway but yeah you're right right like the mirror the mirror of it and that's the tool of it and that's a really hard thing to convey because what people are used to is putting words in a box like with Google and getting a response and being able to like trust and evaluate that response instead. You're putting words in a box and it's translating your idea into another form and that is simply going to mirror what was inherent in the idea as according to the rules of the lm as opposed to actually being an answer to your question but it's suspiciously like an answer and so this is such a subtle thing. And again this is where I get if you ask me kind of what going back to harms the greatest harms that the lm companies do and I actually think that anthropic does a better job here is to anthropomorphize the bots. That has caught like the fact that it looks like it's answering rather than statistically translating a question into an answer and then that answer into code and then that code into other code if they had emphasized translation as opposed to chat I think we'd be in a much better place with this technology and I think we'd have a better understanding of it. What would that look like and from a UI that in a way that would make sense. You know I think what would be useful is instead of a good question I don't know I'm in a immediate answer but my instinct is you would keep. You know I mean this will be really nerdy but more like a GitHub commit log like you put this in and then I and actually this is what cloud code and other things end up looking like which is here was our state and then I evaluated it and I did a bunch of queries on my internal database and I transformed it into this new state I've saved the old state case want to go back to it but here we are now today so we have a whole new kind of context and we've actually we've changed the way that we're working where do you want to go from here well. I want to do this and I want to do that great I'm going to update the state again and I'm going to keep a really clear log and I'm going to keep the relationships between where I was when we started doing this and where I am now I keep that explicit so that you can learn how this works and how to do this and how to do it repeatedly and how to do it on guardrails and how to do it in such a way that you have confidence that it will be the same today as it was yesterday. And if you gave me that which does an average human being really want that I don't know but I do right and is that going to work better than chat no probably not probably won't get you 700 million users but I think that like elements are complicated. It's really hard to learn how they work I actually had chat UPT write me a medieval quest in which a a magic spell was said tokenized and sent through the different layers of the LLM. I highly recommend it like find an analogy that works for you and then make it explain LLMs in the context of like quest through journey. Yeah because otherwise you don't there's a lot of things that just get go missing like the fact that there's millions of layers happening in each layer is kind of like talking back and forth to the other layers and fit and sort of you're it's not like your question is being answered your question is being broken up and spread across sort of like a zillion meta databases that are then coming back and forming something that looks like an answer. But without consciousness and like that you know I don't know how to explain that to people to see I got I got a savvy there is I so we do a whole other podcast on this but I just want to let me let me respond and then I'm curious what you think and then I think what we should we should definitely do a part two of this conversation but what I hear what I'm hearing is. Do a live event to that before we could record do it yeah we can we can invite all the liberals and they can yell at us as as you said yeah. So what I hear you saying or almost yearning for sounds like traditional code. You know you know what you're going to get you know if you do it today it's going to be the same as it was yesterday or tomorrow it's going to be the same as it was today it's very traceable and I also hear a little bit of like it's not actually giving you an answer it's more of like a six to classic parent type thing. A little bit yeah yeah and my feeling about this is actually we are extremely well equipped to work with the way language models work and we're much better equipped than we are to work with code and for people who are non experts and that's because. The and and I think it's actually good thing that they're anthropomorphized because we have models very advanced models for how to deal with human beings and human beings are like this they are squishy they do not necessarily give you the same answer today as they did yesterday. And there are specific kinds of people that are particularly like language models. So people pleasers as a as a people pleaser. I'm very much like a model. A lot of empathy for my language models that's true yeah and and you you you get that sense from a people pleaser where like. other people pleasers in my life like I can just see when they're kind of like doing that thing where they're just telling me what I want to hear and I'm like stop like I just want to know what you think you know and so I think we have a lot of basically innate biological machinery for dealing with this kind of interaction and that. Yes there's there's an adjustment period and yes like for example if you we should be detecting if you're in delusional state and chat you should not talk to you or it should at least not like you know go along with your delusions right. But I think people will very naturally learn because there's a really close analog they'll very naturally learn to use it and then very naturally learn to separate it from other types of things. And put it in its own sort of category and and and I think that's why I think it is actually kind of genius that it is a chat and it is a little bit anthropomorphized and it is interacting in that kind of way. I don't know I see it I get it I just don't know if we can handle this man I don't know I think the humans are pretty when I'm when I'm talking about making reproducible that's me as a kind of programmer outliner type I get that. But I think what's what's tricky and what's thorny is when you talk to businesses and works. What's it really one is it not ones that are just like trying to figure out what gender to be I means that lack of reproducibility is really scary because they need to know that something. You know what I think what here's what it sounds like you're saying to me and push back on this. Paul it sounds like you wanted to work like computer. But it doesn't work like computer it works like new thing and you should get used to new thing instead of expecting it to work like computer. It's not quite right it's close the the the slight change I would make is it works like new thing that is very close to thing that is older and more innate for you to interact with then computer. And that gives you a lot of innate biological cultural like machinery for how to deal with new thing productively in the way that you actually did not have with computer. And comes with costs it's not cost free you may confuse new thing with person but it is also part of it's part of its power and beauty and part of the reason why it has been adopted so heavily. And makes me optimistic that we will also start to naturally separate out new thing into into a clearly new category that we know how to deal with because we know how to do that with people. We know how to do that with the people in our lives who like act a certain way we know we have to like deal with and that's why actually I think some of the average or some of the news articles or whatever is productive because. It's the only way to or it's not maybe the only way but it is one good way to get people to just like pay attention and just be like okay I got to like be a little bit suspicious of chat to be tea but I'm still going to use it. And so I think that's you know I would write the articles differently I would write the headlines differently but I think what we're trying for is some some way to differentiate between person and new thing but I think that's a productive process that's going to happen. I mean interesting okay I'm puzzling it out because what is my actual my criticism here is that but here's what I want what I want if I am a business or not for profit or I manage a lot of electronic health records. If you want me to use new thing I need to know that it works like computer because I trust computer computer is encrypted and saves the data and it's good. And you're telling me the new thing will let me have more of this but I need to know that it's going to be the same today as it was yesterday as an interface as a way to get to that stuff. And maybe the way to get to that stuff is you get the new robot to write the code and as a result you have this very reproducible environment maybe it can stand up things that repeat. But that ambiguity it's not really just my ambiguity like I think that's the ambiguity that a lot of organizational thinkers are dealing with right like how do I trust this I know I can do stuff with it but how do I trust it. And what you're giving back to me is like at some level feels like you're saying you can't because it's like people. And companies run with people yeah but they love not to see this is the fantasy right so take a second if we have a second and teach this out because I think it's really important. The fantasy of this technology which I think I agree with you is not actually what it's for is that it will give me the interface to human beings but the discipline and predictability of the computer. And that isn't working yet absolutely and what's happening I do think that like open AI is saying just give us a minute just give we're going to get you that we're going to get you the people that you don't have to pay that do exactly what you tell we just need a little more time. And at some level I feel like that's where a GI has and has landed as a as a concept like a cohort of disciplined bots. Do you where do you think we're going and what like I'm saying this I'm sort of watching your face do funny things like what do you think I think well I have a whole AGI take. But the really important thing is do exactly what you tell them and exactly what you tell them is that's the whole that's the whole ballgame like what are you going to what are you going to tell them. And I think the way that our intuition fails us is well if it does exactly what I say it's going to be the perfect thing. And that's actually just not true because you often don't know what to say like it's a process it's a creative process of figuring out what to say with experience with other people with the machine. And I think also there are organizations right that is the actual value of this thing is that it generates constructive confusion. And you have to address it with it but then it can actually you can iterate through confusion and get to goals yeah and that is very very real and it is not saleable that's not what anybody wants to buy. I think that there's so we do a lot of consulting to with big companies and I think there there is there's room for AI inside of big companies however I think it may actually be that and this is this this should actually be a positive thing if you're afraid of AI adoption being too quick is I don't think that you can it's very hard to be totally AI native retrofitting into a big company. I just don't think that that happens really and so even though explain that because I mean literally that's kind of we're trying to build that bridge and it's hard I think I know what you're talking about. The exact thing that I'm talking about is exactly what you're saying exactly what you're saying which is like well they wanted to be predictable and do the same thing today as it did yesterday and that's just not how this technology is. And so at its best like I think there is a way to make things very predictable but you're saying like at its best yeah at its best that's not what it is. And so so big companies can use this and can start to adopt it but because they have all these forces and constraints that make it difficult to use things that can't totally be trusted and are totally new. I don't use it to it to its maximal extent but I think so I think that will lead to less change than might be intuitive to those of us who are sitting around at Thanksgiving being like holy shit like always for five just change the entire world. I have this to be constantly with my business partner because I'm like man that's it death is coming. You've seen bureaucracy and he's right like I worked with some of the largest bureaucracies in the world takes a long time. I once we were up for a project with America like years and years ago Obama era and they're like God if you guys could do it we could give you 20 grand if you could just like take an MX and we're like we'll do it we'll help America. And then like a week later they call back and they're like now it's going to give the Navy $2 million and it was for like essentially a glorified RSS feed reader like it wasn't. No it would have been like a $50,000 project we're going to take a hit but but it's madness right and so like the largest bureaucracies have never had a sense of value. Being and money sort of like and the actual delivery being all that we all that connected as much as like an individual developer might feel so I think. Excuse me I think you're not going to change that I think that is right. The only thing I think though Dan is like. I want to I want to finish though because I think there's there's there's this other there's this other component of that which is pace change slower but companies like ours that are right now are about 20 people. Like sub 20 people that are growing up in this world where every single person is using cloud code across the organization for every single thing. You're you're creating all these new primitives for how to work with the squishy technology that is not about how do we make it like so predictable that it doesn't take risks it's like how do we do the most we possibly can with it because. Because we're we're small enough and young enough that we can take those kinds of risks and those kinds of companies I think there's only small number right now but they are going they're going to be a lot of companies like that over the next five or 10 years and they're going to become big companies and be acquired by big companies and so that's the. That's the other side of it is instead of trying to make the technology legible to someone who's like running a multi billion dollar company. You can you're actually going to get the best out of it by making it like the most useful thing for these this like small group early adopters that are figuring out like how do we use the squishiness to our advantage. Yeah I mean I think I think there's going to look it's like anything is it's so big and this space is so big it was already so big and we're dropping such a big change into it. That it's going to express multiple different ways like I do I like I completely buy that there will be lots of AI native works especially now that plot like I'm seeing cloud code like the actual promise future of accelerated delivery is here like you can. I mean our thing too like you can build a business app in like five minutes and it used to be five months so like and that's true of 3D rendering and that's true of like all these categories that were really really complicated before. And so I think they'll be this huge well layer of acceleration from relatively small organizations that can deal with that take it and learn it and apply it and and have a desire to like share the value they want to like do more get paid less but move faster. Like there's huge opportunities there I think where people are screwed is if they're like cool now I can engineer 10 times faster I'm going to go on vacation and I'll just get on my work done like five minutes and nobody will know that is going to come by you but I also do I think though. It's too big of a change and people are going to want some of that for themselves like I'm just sort of thinking about really big orgs I've worked with were the engineers just say no all the time. And the CEO is really frustrated but that's just life that's just how it goes that's what it's always been like and then somebody shows up and they're just like it doesn't have to be that way you know you can have everything that's going to feel so good. And they're going to throw it by the way side it's going to be like a live live love kind of like trip to Italy for them they're going to just you know they're going to abandon their family because they can suddenly like the supply chain SAP integration that was scheduled for 36 months now takes three. Oh my god I just got the other the other thing too and I'm sorry to get corporate but like SMBs can't afford big enterprise software but they also like don't have CTOs like they still know what to do in the middle. And they can have really good tools now they can like which means for them that instead of implementing sales force they can buy a summer home like it's like that that's sort of where that equation plays out so I don't think. Because what you're saying here is is all true up until the point that you realize that a vast amount of spend on technology goes to like five companies and everybody kind of hates those five companies like. Unless they make money from them they hate them like they come to us and they say I hate this company and I will do anything to never work with their software again. And so like given that being out there I think there's a lot of drama ahead as people decide if they want to spend millions of dollars on SaaS or not and and sort of heavy enterprise builds so. I think it's kind of yes to everything as well as status quo because it's such a big space it's not going to change but I think we got to watch the margins I think stuff is going to shift really weirdly in ways that we weren't expecting. I agree and I think that's a great place to leave it Paul fantastic conversation is really great to get to chat with you yeah let's let's let's hang out Dan I would love to do that if people are looking for you where can they find you on the internet. They should check out our website aboard.com we have a really really nice think of it as like super pro vibe coding platform that lets you build stuff but we build it with you we we don't just give you a tool we make sure that like we've good product manager. We call them solution engineers who listen and they will help you out so that's enough shelling. You can send me an email Paul dot forward at aboard.com you can find me on LinkedIn find me on blue sky off the Twitter all the regular places I'm pretty easy to find awesome. Thanks Paul yeah anything you need let me know. Oh my gosh folks you absolutely positively have to smash that like button and subscribe to AI and I why because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard but instead of gold it's filled with pure unadulterated knowledge bombs about chat GPT. Every episode is a roller coaster of emotions insights and laughter that will leave you on the edge of your seat craving for more. It's not just a show it's a journey into the future with Dan shipper as the captain of the spaceship. So do yourself a favor hit like smash subscribe and strap in for the ride of your life and now without any further ado let me just say Dan I'm absolutely hopelessly in love with you.