Why Opus 4.5 Just Became the Most Influential AI Model

The world changed last week—Opus 4.5 is the best coding model Dan has ever used. It can keep coding and coding autonomously without tripping over itself—and it marks a completely new horizon for the craft of programming. The dream is here: You can write English, and make software. We had Paul Ford on AI & I to talk about it. Ford is the co-founder of Aboard and also a prolific writer. He authored one of Dan’s favorite pieces of technology writing What Is Code?—so he’s the perfect person to unpack this with him. We talk about the wonder—and genuine unease—that comes with using tools this powerful. We also get into what people who love technology should care about as the ground under us shifts faster than we can imagine. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: ⁠https://every.ck.page/ultimate-guide-to-prompting-chatgpt⁠. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: ⁠https://every.to/subscribe⁠Follow him on X: ⁠https://twitter.com/danshipper⁠ Head to ⁠ai.studio/build⁠ to create your first app Ready to build a site that looks hand-coded—without hiring a developer? Launch your site for free at ⁠Framer.com⁠, and use code DAN to get your first month of Pro on the house! Timestamps: 00:00:00 - Start 00:01:57 - Introduction 00:03:28 - How Claude Opus 4.5 made the future feel abruptly close 00:08:12 - The design principles that make Claude Code a powerful coding tool 00:10:57 - How Ford uses Claude Code to build real software 00:20:12 - Why collapsing job titles and roles can feel overwhelming 00:22:56 - Ford’s take on using LLMs to write 00:24:09 - A metaphor for weathering existential moments of change 00:25:45 - What GLP-1s taught Ford about how people adapt to big shifts 00:49:36 - Why you should care what your LLM was trained on 00:52:15 - Ford prompts Claude Code to forecast the future of the consulting industry 00:59:18 - Recognize when an LLM is reflecting your assumptions back to you 01:12:39 - How large enterprises might adopt AI Links to resources mentioned in the episode: Paul Ford: ⁠Paul Ford⁠Ford’s company Aboard: ⁠https://aboard.com/⁠The piece Ford wrote for Bloomberg in 2015: ⁠What Is Code?⁠Alan Kay’s concept of a personal computer for children: ⁠https://en.wikipedia.org/wiki/Dynabook⁠

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Dan Shipper?

  The world changed last week. Opus 4.5 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, it fixes it.

• 0:12Speaker 01

  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 no longer feel like I can in good faith say, human skills are going to be relevant. One way to look at this and be like, hey, you can take your craft. You can evaluate the outputs of 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. But 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 to. So that part's tricky. I think what's wild to me is learning how hard it is for humans to metabolize change.

• 0:57Speaker 01

  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.

• 1:28Speaker 02

  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.

• 1:57Dan Shipper?

  Paul, welcome to the show.

• 1:59Speaker 01

  It's great to be here. Thank you.

• 2:01Dan Shipper?

  I am so excited to get to interview you. You, for people who don't know you, you're the co-founder of a board, which is a AI-powered software delivery platform for businesses. But closer to my heart, you are a fantastic writer.

• 2:15Speaker 01

  Thank you.

• 2:16Dan Shipper?

  You wrote a piece, like when I was in college, that like, just, it was like, it's like the piece 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, but-

• 2:28Speaker 01

  You were in college a mere 10 years ago. Oh, Dan, that's fine. You drink some milk and talk to me here, then that's great.

• 2:39Dan Shipper?

  I have to do stretches now. I didn't have to do stretches before. Yeah.

• 2:43Speaker 01

  At least you can do the stretches, dude. Enjoy it.

• 2:48Dan Shipper?

  So, super excited to talk to you, but I think the thing that we are both super excited about is Claude Code. And in particular-

• 2:58Speaker 01

  Well, wait, wait, I'm super excited about my own product. Well, but yeah, Claude Code. Let's talk about it, dude. Know what the hell just happened?

• 3:07Dan Shipper?

  Yeah, the world changed last week and I think people-

• 3:11Speaker 01

  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 can you, can, what do you think it is? It's Opus 4.5 and Sonnet 4.5. Inside of Claude Code was a step change. How would you describe it?

• 3:28Dan Shipper?

  I will say, the, 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 like, looks like a passable app. But Opus 4.5 is the first time where I've, I've been able to vibe code and it just keeps going without tripping over itself. Like, it just keeps building stuff and it, it, it doesn't have errors. If there are errors, it 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 little pictures of books I'm reading and it will do a, 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

• 4:10Dan Shipper?

  reading study of it and then it'll generate a custom introduction for me and a, and a custom reading profile based on all of the stuff in my photos. Like, it's, it's crazy. It's a fully featured app that would have taken months to build that I have no idea how it works. And that's just a new world. I'm curious what you're seeing.

• 4:29Speaker 01

  Very similar. It's so I've been, we have a tool that built, 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, you know, trying to wrap guardrails around the chaos of vibe coding because it doesn't finish things. It's the last miles really long. It tends to leave a lot of loose ends. And 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, they sort of released their models. And I think what I would say is that Claude Code is, I would go so far as to say it's the first true product built on top of an LLM. There are a lot of, and you know, I want to believe that we're in there too and so on. But what we're all

• 5:12Speaker 01

  trying to do is, 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 expected to without all the sort of strange endings. And Claude Code feels like they, 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 Sonnet and Opus are better, but they're not like 9,000 times better. But they, 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

• 5:57Speaker 01

  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 document, it's 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 when, and what's the gender and race breakdown at the school? What is tuition and so on and so forth. And

• 6:31Speaker 01

  The 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 like it was a horrible, horrible program, programming problem to sort of take this, transform it and put it on the web in a, in a sort of modern way. And, and I'm, man, I just knocked it out. It wasn't easy. Like I still had to 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

• 7:12Speaker 01

  and it did it in 20 minutes. Right. And it's just sort of like, no, I, I spent whole days creating that pipeline, right? But that used to be like the work of a company. And, 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, 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. This is, this is me trying to come up with analogy that connects with you as someone who's a lot younger.

• 7:50Dan Shipper?

  Thank you for being so relatable.

• 7:52Speaker 01

  Yeah, this is part of my job.

• 7:56Dan Shipper?

  I think I totally agree. My experience, some of the, I've been, I actually did a whole like presentation for our team this morning on like 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, the thing that is really interesting, the, the, the design principle that I think made Claude code makes Claude code so powerful is that anything that you can do on your computer, Claude code can do. And it has a set of tools that are below the level of features. They're like, they're low level tools. They're like files, like they're grab, they're command line tools. It's bash, it's grep, it's like all this stuff.

• 8:42Dan Shipper?

  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 means that the, the programs or the features of Claude, Claude code are actually just prompts. They're slash commands and subagents. 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 there's, I think that that is a general principle that you can start to apply to any AI based application as a, as a product principle, which is anything in

• 9:26Dan Shipper?

  our application, AI, 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 we, the agent uses low level tools to accomplish the feature outcome. And that opens up all of these like interesting, cool, new doors for software development.

• 9:50Speaker 01

  I agree. Look, I think the patterns in this kind of programming, this kind of thinking are really, really different. So I'll give you some, some Claude examples, but frankly, as someone, as a company that's like building a tool along these lines, I think the patterns are, are emerging kind of for everybody and sort of all the LLMs. It's just that Claude code just really bundled them up very, very efficiently. And it kind of hit its core audience of engineers, which is them, like just like right, it's just a slap across the face because it's like, they literally were like, Here it is. Here's the future. It's gonna look like this. And we all went, yeah, all right, man.

• 10:25Dan Shipper?

  You got it.

• 10:26Speaker 01

  Yes, yes, Mr. Claude. There's a few patterns, right? So A, yeah, everything you're saying, like you're bundling stuff up as sentences. There's another aspect of any, and it integrates with the existing system. So it's not like, it's not this world apart. It's an, 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 into Claude, right? Like I'm just, it's, it's so immediate because it's so much better at building and orchestrating. And you know, it's funny, it really, 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 like fly.io, which is a very fast deployment environment. And I was like, you know, because I bet it'll

• 11:08Speaker 01

  be able to coordinate well here. And then I just was like, wait a minute, I have this random ass server, just like sitting somewhere that I use for scratch projects. Can you just SSH into that and just deploy this thing for me? And it's like, yeah, no problem. And it just like jumped onto the boxes and like looked around like, I don't know, it's an Ubuntu server. Yeah, let me update your engine X. Oh, 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, and cutting and pasting into Google Sheets. And I'm like,

• 11:53Speaker 01

  is it all available on the web? And he's like, it sure is. I open up Claude code on my phone and literally between turkey and dessert, I built and shipped it. It was SQLite on the backend. 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, like I shipped a pretty complicated search based, full text search. Like I know that whole architecture really well. So it's 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, so there's all of that going on. And, and I think that as I've been working with it, what I'm finding is, is

• 12:41Speaker 01

  You gotta 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, 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 Claude, you have to calm down because your code's okay, but it's not that great.

• 13:25Speaker 01

  I want you to go find all the open source libraries that are really good about digital signal processing, which is really edge casey. 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, 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.

• 14:07Dan Shipper?

  Yep, I agree. I want to stop you there at the, like the sort of emotional level of 200 years as a software engineer.

• 14:17Dan Shipper?

  And I think that there's probably, there's, there's just a lot of people who are professional, who are professional software engineers who love the craft of code and who maybe are pretty skeptical of AI because they're like, well, I can't write like the, the well crafted code that I can write. You know, it has, it does all these things, like 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. There's all this like stuff, right?

• 14:50Dan Shipper?

  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?

• 15:05Dan Shipper?

  How do you square that sort of like craftsman mindset about code with what is now possible?

• 15:11Speaker 01

  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,

• 15:21Speaker 01

  I gotta tell you, I mean, I've been watching all this stuff real closely and I know how LLMs work. I did the homework and so on and so forth. And I kind of knew we were headed in this direction. But again, it's like, it's a step change in product. It's not a step change in technology. Like, the technology is still roughly the same. It just feels like they're, but there, but there's also this element of like, one of the, 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 Anthropic, 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,

• 16:05Speaker 01

  which means it can accelerate. And so what I'm getting at is I no longer feel I can in good faith say, hey, calm down and take it as it comes. Humans are, 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, you know, 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

• 16:49Speaker 01

  take your craft, you can evaluate the outputs of 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 are just like, 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. Like, they might be crap. You might be looking at this and you might have like 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 like, it's not like, there's no API glaze. It's like it pulls from the database or it doesn't. So it's just this very confusing moment where it's doing really practical, really difficult things. It used to be really expensive.

• 17:32Speaker 01

  And all I can tell people to do is like, somebody on Blue Sky, I don't know who was, just was like, which you know, 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. Like, you gotta just give it two hours and see where you get. And then you can be as grumpy as you want, but like, you gotta give it a go.

• 18:00Dan Shipper?

  I agree. I think, and I would love to get to some of the like 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 like 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.

• 18:26Speaker 01

  You know, it's funny, I'm building an 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.

• 19:10Speaker 01

  You know, like engineers say no 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 gotta say no upfront. And my, my co-founder has a wonderful maxim, which is there's, 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. 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, but they freak out.

• 19:52Speaker 01

  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, who 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.

• 20:34Speaker 01

  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 fricking smack across the face.

• 20:48Dan Shipper?

  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. With the recent launch of Design Pages, a free canvas-based design tool, Framer is more than a site builder. It's a true all-in-one design platform. From social assets to campaign visuals to vectors and icons, all the way to a live site. Framer is where ideas go live from start to finish. Design, CMS, and publishing, all on one canvas. No handoff, no hoping the final version looks like your mock-up.

• 21:33Dan Shipper?

  What you make is what goes live. Framer isn't a stripped-down demo. It's a free, full-featured design tool. You get vectors, 3D transforms, P3 colors, SV animation, unlimited projects and collaborators. Are you ready to design, iterate, and publish all in one tool? Start creating for free at framer.com/ design and use the code DAN for a free month of Framer Pro. That's framer.com/ design and use the promo code DAN. Rules and restrictions may apply. And now, back to the episode. It's interesting. I've definitely, 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?

• 22:16Dan Shipper?

  That it has quickly shifted to like, there's so much to do. So, so it's, I think I'm familiar with the emotional experience.

• 22:25Speaker 01

  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 not-for-profits in and lots of folks who like 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. Like, we're coming on, we got GLP's pandemic and now this.

• 22:56Speaker 01

  Writing is funny for me too, because I'm like, I actually see the writing is because like, it doesn't write for me. I kind of don't get it to write for me. It just, it can't be me. Like, 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. Like, and I'm like, it gives them access to a world and to kind of entree into a more formal style of communication that they didn't have before. And so like, to me, writing is supposed to empower. And like, if the robot helps you, that's good. If the robot thinks for you, that's bad. So.

• 23:27Dan Shipper?

  Yeah. I think I've been trying to sort of process like, okay, what are the, what are, what are those moments where I had that existential freak out? What is that like? Because I had that a few times, sort of 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 like, 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

• 24:06Dan Shipper?

  next? And the intuitive experience that I think matches to this most closely is before we had really good sea travel, we used to think that if you, if you went into the ocean, there would be like an edge that everything would fall off. There's, there's, 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. And 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. And there's like, it's a cliff, and it's just going to like, drop

• 24:48Dan Shipper?

  off. And then each time I sort of step over the horizon, and I'm like, whoa, there's this whole new territory, which is not to say that there are no bad effects and, and, and there's, there's not like complicated social issues to, to work out. But it is to say that.

• 25:07Dan Shipper?

  I've learned to catch that edge of the world intuition and try and I've tried to update it with there's probably not an edge. There's just a new horizon.

• 25:17Speaker 01

  That's a good way to look at it. I agree with that. I think for me, it doesn't. 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. So that part's tricky. But I think what's wild to me is learning how hard it is for humans to metabolize change. For me, the moment,

• 25:45Speaker 01

  the one that blew my mind is the last time I felt this way, just like exactly like this, was my doctor put me on Manjaro very early. I needed it.

• 25:56Dan Shipper?

  What's Manjaro?

• 25:57Speaker 01

  It's like Ozempic. It's a GLP-1. Okay, so suddenly, after a lifetime of not being able to lose weight, I lost like 70 pounds in a hurry. And I was very dangerously big. I'm still pretty big, but like, my health changed. And it was really after a lifetime of being told, like, 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 are all these rules in this whole social system and things that I heard from doctors. And it was one day, they went, 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

• 26:42Speaker 01

  are the only ways that things can change. And then to hear the next day that, actually, it kind of was a 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. Like, I just like, I knew in that moment, like, 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's 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 a year or two, which is how long it's going to take for like 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.

• 27:27Speaker 01

  Like it's just nowhere near and it's actually going to look like that horizon. It might take a couple of 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 forums or Google spreadsheets that are floating around. Like my, 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 OpenAI is going to build their own and you know that Copilot's going to get smarter and you know that there's going to be Super Bowl ads, if not this year, then 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?

• 28:12Speaker 01

  Like software is eating the world was this whole idea and now it's eating itself. And, and so like, I do, look, you're right. Like, are we going to, are we going to be okay as a species? About as okay as we ever are. Will there still be jobs? Yes. Right? Like I, 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've, we just created the number one change accelerator possible, which is move

• 28:55Speaker 01

  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.

• 29:09Dan Shipper?

  I love the GOP one example. And it's interesting that you listed GOP ones with Trump and the pandemic. But I assume you're, which, you know, in my world, those are two pretty negative things, but GOP ones, I assume you're

• 29:25Speaker 01

  I'm a big fan.

• 29:26Dan Shipper?

  Positive. You have a positive experience with them. So it's sort of interesting.

• 29:29Speaker 01

  Change is hard, man. I was in client services for 20 years. It is 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, and it's not me saying I want you to use this. I literally just want to say, and it was like this when I was writing, I just want to show you so that you can figure out what to do next. And 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.

• 30:14Speaker 01

  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. Like 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 app builders? And like, everybody's having the experience you and I are having, who is deep in on this.

• 30:58Speaker 01

  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, 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.

• 31:25Dan Shipper?

  Isn't that interesting? Like, I've been thinking about that, too, a little bit is, if I take a step back and like, re-round 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.

• 31:40Speaker 01

  Yeah.

• 31:40Dan Shipper?

  I would have been like, that's great. That's definitely.

• 31:43Speaker 01

  Finally happened. Yeah, they've been promising this. They have been promising this for 70 years.

• 31:49Dan Shipper?

  And then it just happened. And then you're like, like, it makes me question, if anything could happen, that would be an unalloyed good.

• 31:59Speaker 01

  Hmm. No, that's been the lesson of the last like 15 years. No, is the answer. And that's,

• 32:06Speaker 01

  I don't know, like, that's also the lesson of adulthood. Right? Like, 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.

• 32:23Dan Shipper?

  Yeah.

• 32:25Speaker 01

  You know, because I get distracted. The,

• 32:30Speaker 01

  you know, it's funny that I'm tangential to that. The promise of software, if you go back to like the Xerox PARC 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. That was the whole point of like Alan Kay and the DynaBook in 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 PARC. Go look at the Wikipedia page. It's it's kind of what we thought. And then we thought that was going to be the iPhone, right?

• 33:11Speaker 01

  We thought that was in particularly the iPad to the point that like Steve Jobs and Alan Kay were were kind of like talking about that in the as the iPhone was being rolled out like, hey, I think we're getting closer, you know? And it was the idea was you'd you'd manipulate code in ever more abstract ways. And what happened is L L Ms, 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 them right now. But like that people have been trying for decades. And so suddenly we have it. We have the fantasy of the 70s. I could sit.

• 33:56Speaker 01

  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 could 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 it's Thanksgiving weekend as we're like just ended and I just spent too much time on the computer, I think.

• 34:32Dan Shipper?

  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 a as opposed to like a little bit more.

• 35:10Dan Shipper?

  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,

• 35:34Speaker 01

  Oh, okay. I know exactly what you're talking about here. I see it differently. So you've got a variety of discourses, right? So 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. Like, that's my, my family, the way I was raised.

• 35:54Speaker 01

  You've got one group that is like, AGI is coming. Get ready. The computer is God. Okay. And so like, we've all kind of learned to make our peace with them. They don't live here in New York City. We're just gonna like, they seem good. It's a lot of guys, a lot of polyamory, and good for them. I wish they would-

• 36:12Dan Shipper?

  Acro yoga, you know?

• 36:13Speaker 01

  Yeah. And they also really like, they've also kind of all shut up about AGI because there, there's so much money to be made. Like, you know, Sam Altman cracks me up, right? Because he wants to be Steve Jobs, but he's Steve Ballmer. He just kind of got the wrong Steve. And, and it's just like, here we go. Okay. Commerce, capitalism-

• 36:29Dan Shipper?

  That is a hot take.

• 36:31Speaker 01

  I mean, am I wrong now? Tell me if I'm wrong.

• 36:34Dan Shipper?

  I, I would love for you to unpack that. I think that's a, I think it's a great, it's a great line.

• 36:41Speaker 01

  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 AI 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 Anthropic, it's funny, if you compare the two companies, like, OpenAI is very much Microsoft, like, whatever you want, whatever you want. We're gonna sell this to you and you're gonna have it. Hmm, 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-

• 37:17Dan Shipper?

  I thought you were gonna say Anthropic is Apple.

• 37:19Speaker 01

  No, nobody's Apple, because nobody's really, Claude Code is great, but it has nothing to do with human beings. It has to do with, it's still for engineers.

• 37:30Speaker 01

  You can't put anyone, you can't put a civilian in front of that interface. It makes no sense.

• 37:35Dan Shipper?

  That's true.

• 37:36Speaker 01

  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 OpenAI wants to make a play for the whole shebang. They want to be the operating system. And the Apple in the middle, the people like, what's it gonna look? The thing about Apple is it made the computer disappear. So who's gonna make the LLM disappear? Right? And just sort of align it with what people want to do today. And I don't know if we're even there yet with this technology.

• 38:12Dan Shipper?

  I don't think so either.

• 38:14Speaker 01

  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

• 38:26Speaker 01

  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 panicked. And the harm frameworks weren't clear. And I think what we gotta 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.

• 39:01Speaker 01

  I, I think you gotta just like, let them burn it out. There will be people who just hate this shit for the rest of their life.

• 39:10Speaker 01

  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.

• 39:20Speaker 01

  I got my kind of progressive type literary types from my, you know, I 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 prose 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, okay, like, that's what they want. Then I think there's, but then there's this very tricky thing going on. There's a lot of people who are like, this is just an unalloyed evil, and we have to reject it. And at the same

• 40:01Speaker 01

  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 do-gooders and climate types who are like, this can accelerate our roadmap, 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

• 40:46Speaker 01

  do more of the other thing we want to do, which is, we believe in unalloyed good for the world. And they're super excited and 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 outright. 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.

• 41:28Speaker 01

  And I get that. I actually think that's right. Like, good. Okay, draw that line. Make them figure it out. They're gonna 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 gonna second guess you. I respect that. So I think it's trying to find a balance in 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.

• 42:11Dan Shipper?

  This is why I stay off of Blue Sky. I can't imagine, I can't imagine being you on Blue Sky. It's like, it sucks.

• 42:19Speaker 01

  I get a funny hall pass with this stuff because I'm an old, and you know, I'm just like, I just, I still get yelled at on a regular basis. But yesterday, I was just like, Simon Willison, who I'm guessing many of your listeners should know, is just like, wow, he sort of stirred the hornet's nest by talking about how AI was changing coding. And I just did a like, he's right, you should listen post. And, you know, like, half the people, 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 that. Let them fight, man. Let them fight in your mentions.

• 42:54Dan Shipper?

  I think this is actually a very typical, um, 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 gonna keep doing it. And it's the same thing.

• 43:14Speaker 01

  It's such a sad day. You also got people coming in from the West Coast telling you how it must be done forevermore.

• 43:19Dan Shipper?

  Yeah.

• 43:20Speaker 01

  And that's, it feels real bad. And they 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 upset? This is really cool technology. And then, and then. You know, it's like, well, because I was gonna make my living as an illustrator and I was gonna send my children to like, you know, we were gonna go on vacation once. And they're like, oh, whatever, UBI. And like that, that whole thing, that's how that comes across. It's just this tin ear on the West Coast. And it is pretty hard for people, I think, to be told over and

• 44:02Speaker 01

  over how they're, it's okay that they're being devalued without being celebrated in any way. 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 gonna use what power they have. And one of the powers they have is to just complain. And I don't know, I think you gotta, we have to own that because we got to keep all the money.

• 44:33Dan Shipper?

  Well, let's, let's, let's, let's unpack that a little bit.

• 44:36Speaker 01

  Okay. First of all, here's me. Let's bring in some employees to unpack it with us as the, as the leaders of our companies. Hey, guys, come on in.

• 44:47Dan Shipper?

  What I want to understand, what I want to say, 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. I don't want this, right? But

• 45:01Speaker 01

  Doesn't help that they all went to the White House and kumbaya'd with Donald Trump, including Jensen Huang. I mean, it doesn't like, help the vulnerable people feel less vulnerable. Let's just, just putting that out there. Anyway, go on.

• 45:12Dan Shipper?

  That lost my mom, which is

• 45:15Speaker 01

  For real, right?

• 45:16Dan Shipper?

  Yeah.

• 45:16Speaker 01

  Yeah.

• 45:17Dan Shipper?

  But

• 45:17Speaker 01

  Dan, what are you doing in league with Satan?

• 45:21Dan Shipper?

  You're, you're, you're replaying my Thanksgiving conversations. No, my mom is much, much, she's very proud.

• 45:30Speaker 01

  She should be, she should be very proud.

• 45:32Dan Shipper?

  But she wants me to be careful.

• 45:34Speaker 01

  You better be careful.

• 45:35Dan Shipper?

  See, eating with the league.

• 45:39Dan Shipper?

  I think, um, but let's, let's annoy ourselves, you know, in between worlds type people.

• 45:46Speaker 01

  Okay.

• 45:46Dan Shipper?

  Where we like the tech stuff and then we also care a lot about writing in the humanities. And so, um, ideally, uh, because we're amazing New York tech people, we can, 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 explain.

• 46:05Speaker 01

  Literally, we, you and I can do an event, have a nice space, we can, we can bring them all here.

• 46:10Dan Shipper?

  I would love that. That would be amazing.

• 46:12Speaker 01

  We're gonna do that. We're gonna do, um, we're gonna do an event where humanities people can come yell at us.

• 46:18Dan Shipper?

  I, I didn't sign up for that.

• 46:21Speaker 01

  You get the. We're doing it. We're gonna bring in the angriest, overpaid professors from the most expensive schools in America to tell us how bad we are.

• 46:32Dan Shipper?

  Here's what I want to understand. What, like, let's just, let's take the, the balanced 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, um, being bad. And, um, like, what, 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, um, a reasonable person who loves this technology should care about?

• 47:04Speaker 01

  That's a very good question. Let me think for a second before running my mouth.

• 47:10Speaker 01

  Because I think, look, there are a lot of stories and narratives about specific harms. You see them in the paper. Um, and, you know, it'll be, uh, chat GPT encouraging suicide in teens. And I think there's an element, I have a, I have a tricky reaction to that because of, as a technologist, I've watched, and I'm, I'm, 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 that, and I think what happens

• 47:54Speaker 01

  is you see these orgs, 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, this is, 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? It's just sort of like, that's, no, but I really think that that's like them asserting, they, they're so, they feel so attacked and they feel so vulnerable because people keep telling them that they're

• 48:39Speaker 01

  kind of evil, that they're like, I'm going to become a fricking cage fighter and that's going to show them. And, 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, 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

• 49:22Speaker 01

  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 L L M's back in the box. I would say that when we're talking about harms, not specific harms,

• 49:40Speaker 01

  The lack of provenance is bad. I would like to know what goes into my meat. Okay, like I want, I want, 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, 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 that Google made 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.

• 50:23Speaker 01

  Oh, you and I are, you're drinking a Spindrift Tropical Lemonade.

• 50:26Dan Shipper?

  Love it.

• 50:27Speaker 01

  Looks like I am too.

• 50:30Dan Shipper?

  Great minds.

• 50:32Speaker 01

  Spindrift.

• 50:34Dan Shipper?

  The brand of New York liberal tech nerds.

• 50:37Speaker 01

  God, it's so bad. So bad. Um, it's terrible place to be in technology, New York.

• 50:46Speaker 01

  So anyway, coming back to it, right? Like,

• 50:51Speaker 01

  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?

• 51:05Speaker 01

  A 50 million person underpinning of the entire global economy, the tech industry. You've got giant consulting firms, you've got consult, uh,

• 51:16Speaker 01

  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, the AI folks are gonna be like, it's great. It's the best thing ever happened. Everybody gets their software. I'm gonna say that because I, I'm building a product along those lines. But like, if we're gonna have this level of change, it almost feels like you're not even, what, what I think is gonna 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, Dan, I, like,

• 51:51Speaker 01

  Because people are like, well, you're still going to need engineers for this and you're still going to, everybody is like, well, but when they see this new technology. And I think we have to start internalizing. Actually, horizons aside, this will change a lot of the ways that 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 write me little stories.

• 52:23Speaker 01

  What's that?

• 52:24Dan Shipper?

  What'd you get? What did it say?

• 52:26Speaker 01

  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 computer science.

• 52:44Speaker 01

  One after the other, it was like, how to draw a Sankey chart? I can share it with you, you can share with, like, it's, I published it as an artifact. Here, let me just give it to you. Let me, let me, let me show you this thing.

• 52:54Dan Shipper?

  Please.

• 52:55Speaker 01

  Hold on, because I want you to, I want you to see it.

• 53:00Speaker 01

  One sec.

• 53:03Speaker 01

  There we go. You see that?

• 53:06Dan Shipper?

  Yep, I do.

• 53:08Speaker 01

  Okay, so this is, I didn't give it this title. And in fact, I tried to really hedge. I was like, hey, it looks like AI might really change the consulting industry. And I want you to make a Sankey chart and tell me.

• 53:22Dan Shipper?

  What is a Sankey chart?

• 53:23Speaker 01

  It's one of these guys. Okay, so it's like.

• 53:27Dan Shipper?

  Chart.

• 53:27Speaker 01

  Yeah, yeah. Stuff comes in on the left, and it gets turned into work on the right. So like, financial services clients, you know, feed in and then they make this much money off of consulting. So right now, we're looking at Deloitte, giant consulting firm, and it does audit and assurance and consulting and tax and legal. Let me zoom in a little bit. Oh, yeah, I just zoomed in on you. Here we go. Okay.

• 53:52Speaker 01

  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. And I, you know, it's kind of ironic to ask Claude. And so I was like, let's look at McKinsey. Everybody loves McKinsey, everybody's favorite company. So $16 billion in revenue, 45K employees, headquarters, New York City. And in 2024, their, their revenue is about 16 billion. Now, I didn't have it do deep research. It was just very hand wavy. So 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.

• 54:31Speaker 01

  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 write employee stories for each company. And so Alexander Torres. Everything right. Oh yeah, everything. Stanford undergrad, Harvard MBA, McKinsey, especially at 27. She was on the partner track billing 800 an hour to tell Fortune 500 CEOs what they already suspected, but needed external validation to act on. 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.

• 55:14Speaker 01

  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 company's 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% as 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 too, and relationships only mattered if you had something valuable to offer. Alex made partner

• 55:57Speaker 01

  in 2029, just as the firm started its long contraction. 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 her client, she left her 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.

• 56:21Dan Shipper?

  Oh, my God.

• 56:22Speaker 01

  Sometimes she missed the intellectual intensity, the feeling of being the smartest people in the room. Then she remembered that the smartest thing in every room now was the computer.

• 56:32Dan Shipper?

  Incredible, incredibly.

• 56:34Speaker 01

  I'll share this with you, so you can share it with your listeners. But it is, it's a Claude Code artifact that I built yesterday for fun. And I shared it with somebody who works at one of the firms. And 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. Mild bearish.

• 57:13Speaker 01

  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 while robots do more for the rest of their lives. And that's not actually how humans and societies work. Like, but, but

• 57:55Speaker 01

  I do think it is a change at that level of magnitude that we're going to have to react to.

• 58:00Dan Shipper?

  I agree. I love, I love that. I think that's so interesting. And I think it's actually a good.

• 58:08Dan Shipper?

  Example of why language models are so powerful and what makes them sort of special. And in that is an interesting example of why I think consulting firms oddly are going to still be valuable and important.

• 58:23Speaker 01

  Let's bring that in. Let's hear what you got.

• 58:26Dan Shipper?

  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, the thing is like, oh, it's not buying analysis and judgment or whatever. But there's something, I want to just stick with the like analysis and judgment for 1% of the cost because like, I have done this too. I have put all of our company financials into Claude and had it write our investor update and it did a fucking phenomenal job.

• 59:05Speaker 01

  Yeah, I mean, that's so good. Anything kind of bureaucratic, it's just magical.

• 59:08Dan Shipper?

  Yeah. And I've also done a lot of strategy stuff with it. And I think that, I think you, 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, it's all that kind of stuff.

• 59:39Speaker 01

  Give me an example, like, just kind of like Excel spreadsheet.

• 59:42Dan Shipper?

  Exactly.

• 59:43Speaker 01

  Okay.

• 59:46Dan Shipper?

  You know, how profitable were we, were this corner is like, 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.

• 59:58Speaker 01

  Make me a pie chart of what we're selling.

• 1:00:00Dan Shipper?

  Exactly. And on the, on the other end is.

• 1:00:08Dan Shipper?

  And the literary analogy is the Borges story, like the Library of Babel, where it's like, every book is there, but there's infinitely many books between where you are and where you want to get to, and they're all nonsense. So you're just always in nonsense, basically, unless you've artificially constrained the search space. The other, you know, I don't know, branch of human thought, or a way to think about the way the world is, is instead of this infinite library where you're sitting in

• 1:00:52Dan Shipper?

  this sea of nonsense, but you know that if you 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.

• 1:01:11Dan Shipper?

  But there are infinitely many books between where you are and where you want to be. It's not countably infinite. It's just, you're just sort of in this enchanted forest of stories that you can go read, and each of them has a plausible sounding answer. And you have to use your own human intuition or judgment 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 mild bear case?

• 1:01:56Dan Shipper?

  I think we're much more likely to be, especially if we're looking at a Claude 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's this other one, where it's like, there is a right answer, and Claude just found the right answer. Because if you change your prompts slightly, you're going to, Claude could write you a great story about why consulting businesses are going to do really, really well.

• 1:02:24Speaker 01

  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 of people from Anthropic. I had 20% left and it's like, hey, we're almost done here. And I'm like, really? Cause 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.

• 1:03:05Speaker 01

  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 LLM, 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, and again, this is where I get, if you ask me kind of what, going back to harms, the greatest harms that the LLM companies do, and I actually think that Anthropic does a better job here, is to anthropomorphize the bots.

• 1:03:42Speaker 01

  That has caused, 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.

• 1:04:02Dan Shipper?

  What would that, what would that look like in from a UI that in a way that would make sense?

• 1:04:08Speaker 01

  You know, I think what would be useful is instead of, it's a good question. I don't, I don't have an immediate answer, but my instinct is you would keep.

• 1:04:18Speaker 01

  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 Claude 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 in my internal database and I transformed it into this new state. I've saved the old state, cause we 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.

• 1:04:59Speaker 01

  I'll 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. It probably won't get you 700 million users. But I, I think that like LLMs are complicated. It's really hard to learn how they work. I actually had ChatGPT write me a medieval quest in which a, a magic spell was said,

• 1:05:44Speaker 01

  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 a quest or a journey. Yeah. Cause otherwise you don't, there's a lot of things that just get, go missing, like the fact that there's zillions of layers happening and each layer is kind of like talking back and forth to the other layers and sort of you're, it's not like your, your question is being answered. Your, your question is being broken up and, and spread across sort of like a zillion meta databases that are then coming back and forming something that looks like an answer.

• 1:06:22Speaker 01

  But without consciousness and like that, you know, I don't know how to explain that to people just yet.

• 1:06:28Dan Shipper?

  I gotta, I gotta stop you there. I, there's, I have so, we could do a whole other podcast on this, but I just wanna, let me, let me respond and then I'm curious, I'm curious what you think. And then I think what we should, we should definitely do a part two of this conversation.

• 1:06:40Speaker 01

  Anytime.

• 1:06:41Dan Shipper?

  But what I hear, what I'm hearing is.

• 1:06:45Speaker 01

  Do a live event too. That'd be fun. We could record.

• 1:06:47Dan Shipper?

  Do it. Yeah. And we can invite all the liberals and they can yell at us as, as you said, yeah.

• 1:06:55Dan Shipper?

  So, um,

• 1:06:59Dan Shipper?

  what I hear you saying or almost yearning for sounds like traditional code.

• 1:07:05Dan Shipper?

  You know, you know what you're gonna get. You know, if you do it today, it's gonna be the same as it was yesterday or tomorrow. It's gonna 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 systematic parrot type thing.

• 1:07:23Speaker 01

  A little bit, but okay.

• 1:07:25Dan Shipper?

  A little of that.

• 1:07:25Speaker 01

  Keep going. I'll, I'll respond. Keep going.

• 1:07:27Dan Shipper?

  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 a 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.

• 1:08:07Dan Shipper?

  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 language model.

• 1:08:17Speaker 01

  I have a lot of empathy for my language models. That's true.

• 1:08:20Dan Shipper?

  Yeah. And, and you, you, you get that sense from a people pleaser where like.

• 1:08:27Dan Shipper?

  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, um, yes, there's, there's an adjustment period. And yes, like, for example, if you, we should be detecting if you're in a delusional state and chat GPT should not talk to you, or it should at least not like, uh, you know, go along with your delusions, right? But I think people will very naturally learn because there's a, a really, uh, close analog, they'll very naturally learn to use it and then very naturally learn to

• 1:09:11Dan Shipper?

  separate it from other types of things, um, and put it in its own sort of category. And, and, and I think, uh, 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.

• 1:09:38Speaker 01

  I don't know.

• 1:09:40Speaker 01

  I see it. I get it.

• 1:09:43Speaker 01

  I just don't know if we can handle this, man. I don't know. I, I think the humans are pretty, when I'm, when I'm talking about making it 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 orgs, ones that really want to use it, not ones that are just like trying to figure out what generative AI means. That lack of reproducibility is really scary because they need to know that something, you know what I think, here's what it sounds like you're saying to me and pushback on this. Paul, it sounds like you want it to work like computer, but it doesn't work like computer.

• 1:10:25Speaker 01

  It works like new thing. And you should get used to new thing instead of expecting it to work like computer.

• 1:10:35Dan Shipper?

  It's not quite right. It's close.

• 1:10:39Dan Shipper?

  The slight

• 1:10:45Dan Shipper?

  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 than computer.

• 1:11:00Dan Shipper?

  And that gives you a lot of

• 1:11:06Dan Shipper?

  innate biological, cultural like machinery for how to deal with new thing productively in the way that you actually did not have with computer.

• 1:11:16Dan Shipper?

  And comes with costs. It's not cost free. You may confuse new thing with person.

• 1:11:26Dan Shipper?

  But it is also part of its 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 outrage or some of the news articles or whatever is productive because

• 1:12:05Dan Shipper?

  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 gotta like be a little bit suspicious of chat GPT, 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

• 1:12:23Dan Shipper?

  what we're trying for is some

• 1:12:28Dan Shipper?

  some way to differentiate between person and new thing. But I think that's a productive process that's going to happen.

• 1:12:35Speaker 01

  I mean, Interesting. Okay, I'm puzzling it out because what is my actual criticism here is that, but here's what I want. What I want, if I am a business or a 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

• 1:13:17Speaker 01

  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, it feels like you're saying you can't because it's like people.

• 1:13:50Dan Shipper?

  And companies run with people.

• 1:13:53Speaker 01

  Yeah, but they'd love not to. See, this is, I know, so this is the fantasy, right? So, take a second, if we have a second, and tease this out because I think this is 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.

• 1:14:17Dan Shipper?

  Absolutely not.

• 1:14:19Speaker 01

  And what's happening, I do think that like OpenAI 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 AGI has landed as a concept, like a cohort of disciplined bots.

• 1:14:43Speaker 01

  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 are you thinking?

• 1:14:50Dan Shipper?

  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.

• 1:15:06Dan Shipper?

  Like, what are you gonna, what are you gonna tell them? And I think the, the way that our intuition fails us is, well, if it does exactly what I say, it's gonna 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.

• 1:15:34Dan Shipper?

  And I think also

• 1:15:39Dan Shipper?

  there

• 1:15:42Dan Shipper?

  there are

• 1:15:43Speaker 01

  That is real, right? That is the actual value of this thing, is that it generates constructive confusion.

• 1:15:50Speaker 01

  And that you have to address it with it, but then it can actually, you can get them iterate through confusion and get to goals.

• 1:15:56Dan Shipper?

  Yeah.

• 1:15:56Speaker 01

  And that is very, very real, and it is not saleable. That's not what anybody wants to buy.

• 1:16:05Dan Shipper?

  I think that there's, so we do a lot of consulting too with big companies. And I think there, there is, there's room for AI inside of big companies. However, I think

• 1:16:18Dan Shipper?

  it may actually be that, and this is, this, this should actually be a, 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

• 1:16:39Speaker 01

  Explain that, because I mean, literally, that's kind of, we're, we're trying to build that bridge, and it's hard. And I think I know what you're talking about.

• 1:16:46Dan Shipper?

  The exact thing that I'm talking about is exactly what you're saying.

• 1:16:50Dan Shipper?

  Exactly what you're saying, which is like, well, they want it to be predictable and do the same thing today as it did yesterday. And that's just not how this technology is.

• 1:17:02Dan Shipper?

  And so

• 1:17:04Speaker 01

  At its best. Like, I think there is a way to make things very predictable, but you're saying like, at its best.

• 1:17:09Dan Shipper?

  Yeah, at its best. That's not what it is.

• 1:17:12Dan Shipper?

  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, it's difficult to use it to, to, to its maximal extent.

• 1:17:31Dan Shipper?

  But I think so, A, 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 O was four, five just changed the entire world.

• 1:17:44Speaker 01

  I have this debate constantly with my business partner because I'm like, man, that's it, death is coming. Just shut up, right? Like, have you seen bureaucracy? And he's right, right? Like, I worked with some of the largest bureaucracies in the world.

• 1:17:58Dan Shipper?

  Takes a long time.

• 1:17:59Speaker 01

  I once, we were up for a project with the, with America, like years and years ago, Obama era. And they're like, yeah, God, if you guys could do it, we could give you 20 grand if you could just like take an AMEX. And we're like, we'll do it, we'll help America. And then, and then like a week later, they called back, they're like, no, we're just 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 were 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

• 1:18:41Speaker 01

  sort of like, and the actual delivery being all that way, 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.

• 1:18:57Dan Shipper?

  I want to, I want to finish though, because I think there's, there's, there's this other, there's this other component to that, which is pace of change is 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 Claude code across the organization for every single thing. You're, you're creating all these new primitives for how to work with this 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.

• 1:19:32Dan Shipper?

  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 the only small number right now, but they are going. There are going to be a lot of companies like that over the next five or 10 years, and they are 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 of early adopters that are figuring out like, how do we use the squishiness to our advantage?

• 1:20:14Speaker 01

  Yeah, I mean, I think I think there's going to be it's like anything. 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 completely buy that there will be lots of AI native orgs, especially now that like I'm seeing Claude Code and like the actual promised 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. And so like, and that's true of 3D rendering. And that's true of like all these categories that were really, really complicated before.

• 1:20:56Speaker 01

  And so I think there'll be this huge layer of acceleration from relatively small organizations that can deal with that, take it in, 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. I think 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 all my work done in like five minutes and nobody will know. That is going to come by you. But I also do, I think, though.

• 1:21:28Speaker 01

  It's too big of a change and people are gonna want some of that for themselves. Like, I'm just sort of thinking about really big orgs I've worked with where 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 gonna feel so good. It's gonna feel so good. And they're gonna throw it by the wayside. It's gonna be like a live, laugh, love, kind of like trip to Italy for them. They're gonna just, you know, they're gonna abandon their family because they can suddenly,

• 1:22:08Speaker 01

  like, the supply chain SAP integration that was scheduled for 36 months now takes three? Oh, my God. And I just got, the other, the other thing too, and I'm sorry to get corporate with it, 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 Salesforce, 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.

• 1:22:52Speaker 01

  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, 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, and sort of heavy enterprise bills. 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.

• 1:23:31Dan Shipper?

  I agree. And I think that's a great place to leave it. Paul, fantastic conversation. It was really great to get to chat with you.

• 1:23:39Speaker 01

  Yeah, let's, let's, let's hang out, Dan.

• 1:23:41Dan Shipper?

  I would love to do that. If people are looking for you, where can they find you on the internet?

• 1:23:46Speaker 01

  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 built it with you. We, we don't just give you a tool. We make sure that like we have good product managers. We call them solution engineers who listen and they will help you out. So that's enough shilling. You can send me an email, [email protected]. You can find me on LinkedIn. You can find me on Blue Sky, off of Twitter, all the regular places. I'm pretty easy to find.

• 1:24:14Dan Shipper?

  Awesome. Thanks, Paul.

• 1:24:16Speaker 01

  Yep. Anything you need, let me know.

• 1:24:26Speaker 03

  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 ChatGPT. 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.