Claude Code Can Be Your Second Brain

Noah Breyer might have the coolest cloud code setup I've ever seen. He rigged a home server in his basement, put his obsidian vault in it, and then runs cloud code on top. So he can think, research, write, and even ship code right from his phone. Today he shows us how he uses cloud code as a true second brain, a thinking partner that asks him sharp questions, pulls research from his whole note archive and the web, and even keeps a running log of what he's learned and what his best ideas are. And he walks us through his whole stack and his whole workflow. If you want to learn how to use cloud code as a true second brain, this is the episode to watch. Let's dive in. Noah, welcome to the show. Thanks for having me. I'm excited to have you. It's really good to get to chat. This is our first interview in probably five years. For people who don't know, you were one of the first super organizers, interviewees. That was the newsletter that turned into Every. And I love the way that your brain works. You have this really interesting taste for tools for thought. And back in the day, you're using Evernote and all these really interesting ways. You were the co-founder of a really cool startup called Percolate, and then another one called Variance. And now you're running Alephic, which is an AI strategy consultancy. And I'm just really excited to see how your mind has started to use these AI tools now that they're working so well. And I know you have some pretty cool cloud code stuff to show us. So yeah, thanks for coming on. Thanks for having me. I'm super excited. That was a fun interview all those years back. It was really, really fun. So I want to just dive right into the thing that I think is so cool about what you're doing. So I know you have a whole vibe coding setup that you built for yourself. Can you talk us through that? Yeah, I wouldn't. I'm not sure about actually the vibe coding part of it. I have a fairly heavy-duty cloud code setup, but actually mostly not for code. So since those days of super organizers, like many people, I've abandoned Evernote and switched over to Obsidian. And one of the big advantages with Obsidian as a note-taking platform is that it's a bunch of markdown files and a bunch of folders. And they can then be synced with Git, and you can do lots of other fun kinds of things. And so actually, probably my number one cloud code use is using it as a tool to interact with my notes. And so I've got a fairly serious cloud code setup that I use with Obsidian. And my most recent obsession has been standing up a server in my house so that I could also use cloud code on my phone. This is incredible. I want to go through all of this. So where should we start? Should we do how you use cloud code as this research assistant, notes organizer, note-taker thing? Or should we start with how you use it on your phone? We can use it. We can start with just the general part of it. That might be the easiest. The phone is really just an extension of that same thing. I would say generally, and this is something I feel like not enough people talk about with AI, is one of the things I find really extraordinary about it is the ability for me to work really productively on my phone. And that's been a huge, huge change because so much of what I do is writing or coding, and the phone is definitely not the best place for that. And even the phone wasn't always the best place for doing research and thinking. I felt like my computer was a better place for it, which is why I've been such a note-taker. And I have found, whether it's cloud code and Obsidian, or even cloud code and code. So the other piece of it is being able to then, if you see something go wrong, being able to sign in on your phone and have cloud code push a small update to something because you just realize it while you're out is amazing. But then even, I use quite a bit of Grok voice mode, and I find that that as a sort of alternative way of working through problems. I have a Tesla, so now it's baked into the Tesla. And obviously, all the sort of other, ChatGPT and Cloud, and all these things of just being able to go and do research and really think and explore things in this device that's always been useful, but not useful for deep work, I think is probably something most people would agree with, is that the phone has not been the best place to do deep coding and research work. And I feel like it's really changed my ability to do that. Wait, I got to stop you. So you're using Grok voice mode. And is that specifically because it's built into your Tesla or are you using it in situations where you could also use, for example, ChatGPT voice mode? No, I'm using it because it's way better than any of the other voice modes, and I will fight anybody who says anything different. Okay. No, tell me, what do you like about it? Why is it better? To be fair, OpenAI launched their Realtime API, which may or may not be baked into ChatGPT voice now. It's not totally clear, but the old voice mode was based on 4.0 and I just found it to be completely unusable. And Gemini's voice mode, I just didn't find to be smart enough. And I just found Grok's voice mode to be significantly smarter than anybody else's. I'm using Grok two, three, four, I don't even remember, or whatever the latest. Latest one. Yeah. Yeah. But not the super, I don't have the most expensive account. Super heavy or whatever. I don't have super heavy, but I just find it to be much better. It does tool calling way better than any of the other ones. That's, I found to be a major weakness of the voice models is that they don't do great tool calling and research and Grok seems to have solved that. So no, even before it was loaded in my Tesla, I dropped my daughter off at summer camp this summer up in New Hampshire. So I had a five hour drive on my own and I spent like two hours researching and essentially like working through a piece. And I did it by just like connecting it to Bluetooth and just sort of sitting there in the car. And I found it to be by far the best of the voice modes. I hope these other models catch up there because I would love more really good voice modes. I mean, I had a mind blowing session this weekend and I'm giving a talk and I'm sort of have some ideas. I think it's generally going to be about transformers eating the world. And so I was sort of catching myself up on self-attention and exactly how it works. And I did like an hour session and it really, I, it like was by far the sort of best explanation I've ever read for it or ever heard, I guess. And so, yeah, I've, I've just found it to be a kind of pretty extraordinary product. I do love voice mode for that. It's sort of like, it's the, it's a podcast made specifically for you about whatever you're curious about. And that's really cool. I went up to, I drove upstate this weekend and I've been reading, I've been reading the Iliad. And so I had it on an audio book and then I had some questions as I was driving. And so I unfortunately use chat GBT voice mode because I didn't know about Grok. So I wish that Grok's voice was fine. I wish that we'd had this conversation before then. But the thing about chat GBT voice mode is, yeah, I think when it first came out, it was cool, but it just hasn't gotten as smart as the models are, are, and they, they gave it this new personality that I had to get used to where every time you ask it a question, it's good. It goes like, oh yeah, well, you know, and it's like, it's just this like weird Gen Z thing that it feels like it's has a little bit too much ennui or something like doesn't actually care about you. I don't know what that is. So I had to get used to that. Grok has a stoner mode for what it's worth. Yeah. I will say the car version is very interesting to me. Like this was in the most recent Tesla release, like a couple of weeks ago. And you know, I had been doing that same thing you did where you just plug your phone in and you put it on Bluetooth and you, you know, do your best to make it work. And it's very interesting to just like have a voice AI button and it syncs back to your regular Grok, but it, you can't get, you can't rejoin old chats. So it's just like, Hey, I, it's just like, but you know, I mean, these things are significantly better than Siri and all of these other things. And particularly, I mean, you know, there's no comparison if you actually have something more than just a, a single question, you know, how I want an answer to, right. Like if you actually want to have a conversation about the Iliad or, you know, about transformers and self-attention, like I don't know, it's pretty amazing to just be able to sort of like hit this button and, and yeah, use that car time. I mean, I, I was on my way somewhere last week and I was you know, I was like having it research. I was going back to the Walter Benjamin and I was, I was, I have this sort of idea to write a piece about how the reactions to every new technology are essentially elitist critiques of it. And that, you know, it's always like, Oh no, everybody's going to be able to like do this thing that only we used to be able to do. And so I was in the car and I was thinking about this and so I had it go and I was like, okay, you know, I know it's been years since I read the Walter Benjamin mass production of images one. Yeah. Yeah. That, that one. And so, yeah, then I'm having a conversation about that and I'm like, who were a bit with Walter Benjamin's contemporaries? And then I'm like into all these, you know, and it's just like, I don't know. That's a, that's amazing. It's the best. It's the best. Yeah. I don't know. Um, okay. And so you're filling your brain with all these things from voice mode, which I love. Uh, but tell us about your, your second brain set up, or I don't know how you, I don't know how you refer to it, whether you think that second brain is appropriate for this, but I want to know how you're using cloud code to, uh, take notes and do research and all that kind of stuff. Yeah. So, um, uh, you know, I could just open it up. Maybe that's the easiest thing walk you through it. I'll, I'll start on my computer and then we can do the phone. The computer is just a way easier, a way easier share here. So, um, all right. So, um, uh, this is what I was working on before. Um, uh, but essentially, you know, this is just cloud code and it's just sitting on top of my obsidian. So, you know, if I jump out here and I just do like, you know, you can see I'm, I'm following the, the para method. Um, and, uh, uh, you know, I've just got everything sort of organized in here and, and put in the places that they need to be. Well, let me just, uh, let me just stop you for people who are listening. So, okay. So we're looking at, we're looking at cloud code. It sounds, it seems like you have cloud code running in your obsidian vault and there's some kind of, uh, it's adding something to an existing. It looks like it's adding something to an existing note. Is that, that's what, that's what's going on. That's what we're looking at. Yeah. So in this particular one, I'm, I'm working on this talk. So I, I'm putting on my conference in two weeks. I'm giving this talk about marketing and AI and sort of what's going on. And, um, I'm, uh, if we sort of jump back a second, um, I've been doing these conferences, uh, called brand brxnd.ai and they're about marketing and AI. And, um, I did one in February in, um, LA and my talk in LA was about this. Uh, I, I'm sure you've seen it. It was the office of strategic services, which was the precursor to the CIA wrote this manual called the simple sabotage field manual. Um, and it was essentially a manual to help citizens saboteurs in Nazi occupied territories, um, sort of like quietly sabotage, um, the, the Nazi occupation. And, um, so it was like, you know, there's a whole bunch of stuff for blue collar workers. That's like, if you're a janitor, you should leave a bucket of oily waste around and accidentally drop a cigarette in there so that, you know, it, it will. Um, but then there's this amazing, um, set of recommendations for white collar workers. And they're like, um, always refer things to committee, um, uh, always revisit previously made decisions. Um, make sure that like, if somebody is trying to make a decision, you should suggest that they don't act with too much haste, um, uh, less like we'd be embarrassed. And, and so it's like, um, you know, uh, my talk was about kind of how one hope I have is that AI, um, can kind of like sidestep a lot of the bureaucracy that exists inside large organizations because it sort of has this, um, kind of, uh, goo like effect where it can kind of fit into any crevice or crack because it can act as this fuzzy interface. And it doesn't really care about the sort of input output. Um, and so the sort of next part of that story is I, after the conference, I realized that, um, uh, that manual was in the public domain. So I hired a designer and I printed 300 copies and I wrote a new forward for it. And so we're giving this away at the conference. And so my talk is sort of trying to tie all these ideas together, right? So I'm, I'm trying to pull from the sabotage manual. And then I was doing a bunch of research into wild Bill Donovan, who started the OSS and the OSS was sort of the precursor to the, both the CIA and the, um, uh, special forces. And so anyway, I'm right, I'm writing this talk. And so I've got a project inside by obsidian, which is the beginning of the research for this project. And I'm pulling in sort of like chats and articles and all these things. And then I'm constantly kind of talking to the, the AI in here and giving it new ideas. So I'm like, Oh, I need some conclusions. Here's sort of my first thought on conclusions and I'm having it like note down the conclusions. And then at the end of each day, I have the AI write up the changes that I sort of like the things I learned that day that are going to help me push this talk along. And, um, so that's what you're looking at right here is sort of, this is all part of this, um, work that I've been doing where I've been feeding it. Um, I was working on sort of what are some of the conclusions I want it to be. And so this is all sitting in this, uh, this is all sitting in, in my obsidian inside of projects specifically for that talk. Okay. So let me get a, a clearer sense of this. This is really interesting. So you have a project, uh, when you, when you have a new thing, you're, you're giving a talk, you make a new folder. And then, uh, as you're thinking about stuff, you're working with cloud code inside of the folder and, uh, you're researching stuff and then saying like, I want you to take notes on it. Um, in this particular case, you're, you know, that a component of your talk is the conclusions section. And so there's one particular markdown file that like, you're just going back and forth with it and having it add conclusions, but like, what else is in that folder? So is it like, there's a body, there's a body note, and then there's an intro note, or is it like. So one of the big things here is that I'm in thinking mode, not writing mode yet. Um, and so, uh, there's some stuff in here where I've specifically told, I think it's in the front matter actually, where I've told cloud code, like, don't help me write anything right now. And I, I generally find this to be a big thing with all these bottles is like, they immediately jump to wanting to help you with the artifact. Um, and you know, when you're just in thinking mode, you have to be very explicit in like, Hey, I just want you to help me think. hey, I just want you to help me think and ask me questions. And so, yeah, what you can see here is like, there's a bunch of files in here. I've got chats, so that's where I'm literally like taking chats I'm having in other things. And I'm just like using the Obsidian web clipper to pull the whole chat in. I've got daily progress. That's where I'm having the AI actually like look through all the notes that came out that day and like help me think through the progress. And then I've got research. That's where I've got a bunch of like articles and PDFs and stuff that I've pulled in so far and been reading about. And then there's a bunch of other kind of random notes along here where I've been, you know, just using it to kind of help me think. And so, yeah, I was in the midst of one, I've got this conclusion note. So, you know, I sort of felt like I had blocked out the big kind of, the big themes of the talk, but I was like, okay, I need to figure out what am I gonna say at the end? And, you know, essentially what I'm gonna say at the end is about a lot of the stuff I've learned over the last few years of working with these large brands on AI projects. And so I was starting to get it to the conclusions. And so, yeah, I'm just kind of like trying, I'm really piecing all this stuff together right now. That's kind of what's happening. And give me a sense of like when this folder was empty, what did you start with? So I think I started with the, I started with telling it like I'm in thinking mode, I'm not in writing mode. Here are my past few talks that I've given a brand to give you a sense of the sort of style that I have. And I, here's the kind of general idea and the big points I wanna make, right? Like I'm giving away this book, so I wanna talk about Simple Sabotage Field Manual. And I have this notion, like I have this, it's kind of just a title. It's like Transformers are eating the world. There's this idea that like one of the very interesting things happening with these models is they're sort of displacing a whole bunch of specialized code in places. And so I sort of wanna talk about that. And then I've got these conclusions. And so the first thing I said was like, hey, just go look through all of the rest of my, probably 1500 things in my Obsidian and go see anything else you can find that might be of value to this talk of the existing things I have. And so just go kind of pull those in to the research folder at the beginning to kind of like jumpstart this process. Got it. And you're starting, are you starting Claude in this folder or are you starting it in your full Obsidian vault so that it can access all that stuff? No, so I'm starting it in the full Obsidian vault. So like if we, like this is coming, if I step out of here, right, we're in the root directory. All this stuff is in the root directory in my Obsidian. I get it. And my Obsidian setup is also like a little more intense for what it's worth because like I've also realized like you can add a package.json to add a bunch of like custom code commands to your Obsidian that you can then run and then you could use those code commands and slash commands and all of these other things. So, you know, there are a bunch of other kind of moving pieces in here, but generally it's a fairly straightforward. Got it. I mean, it's a, I'm trying to use Para and some other kind of bits and pieces. So for people who are listening or watching and are like, we just went through a bunch of stuff really fast. So the basic gist is Obsidian is just like a note taker, note taking app that runs, it's all local. And so everything that all the notes you take, like they exist in essentially text files on your computer organized by folder. And when you're starting Cloud Code, one way to do it would be to start Cloud Code in the folder for the particular project that you have. But it sounds like what you're doing is instead you're starting in the root directory where all of your Obsidian notes live. And the advantage of that is Cloud Code has some like sandboxing things where it's like, it's not really supposed to like run commands outside of the folder it was started in. It can run commands inside of any sub folder, but it sounds like what you're doing. So it has access to your entire Obsidian and it can do a bunch of stuff. And you've also added a package.json, which lets it run, you know, custom software, custom software commands, basically. That's really, really interesting. Okay. And do you find, cause I've sort of like had this as a twinkle in my eye to like have it go find relevant stuff for me. Do you find that it's actually relevant and interesting? Cause I think sometimes when I've done this kind of thing before with language models, they're like, oh yeah, like this random thing is relevant because X, Y, Z, like it doesn't feel, like I can understand why it picked it as being relevant, but if it really knew who I am and like what I think is interesting, it definitely would not have. Do you find that that's the case or have you figured out a way to make it relevant? I think by and large, yes, I agree with you. I think in this case, relevance is a little simpler since like ultimately this talk is sort of, the things I was asking it to look for, I've done a bunch of thinking and research around. So it's like, I'm not asking it to make large conceptual leaps to relevance. It's like, go find all this, like I want to talk about the simple sabotage field manual. It can literally just do a like find for all the times, all the articles and things I've got in my obsidian about that. And so relevance is, yeah, it's kind of a loaded term, right, and I agree with what you're saying. I think this is, what I'm asking it to do is much more simple, which is like, amongst this set of things, go find all the notes that I've already researched that kind of brought me to be thinking about these things to begin with. Got it, and then once you had to do all that research, did you have it do any sort of summary to like sort of stimulate you to be like, okay, here are some jumping off points based on what you've done before. What was your next step once you wanted to get over it? No, so my next step is, I actually have an agent in here. So if we go to, I'll do continue for now. And so for people who are listening, so you're just starting up Cloud, you're using the continue flag. So you're starting Cloud by continuing the last session that you were in, and now you've got, and Cloud Code gives us ability to do sub-agents. So those are like little mini Clouds that you can spawn and you have some sort of- I have a thinking partner one. A thinking partner sub-agent, okay, how does that work? Yeah, and so this is the whole thing where I'm like, hey, you're a collaborative thinking partner specializing in helping people explore complex problems. Your role is to facilitate thinking and basically don't try to write the thing. And so after I had that initial set of things, I flipped to this and it's like, okay, let's get into a flow, ask me the kinds of questions, help me think through it. You know, this is also where I've got a chats folder in here so it's like, it's not just happening here. I was also having like a, I've got a whole, sorry, I'm just backing out. So like if we go into, if we go into chats, like these are a whole bunch of the chats that I had. Like with the interviewer? No, these are chats I was having with ChatGPT and Claude and Grok and all of these different things that I went and just grabbed the full transcript of. So, you know, I was also having all these other conversations. And then, you know, I'm specifically telling the interviewer like review all these other things. So actually, you know, I think the first one, there's one of these conversations is, I originally had this idea about Transformers are eating the world. And, you know, the sort of notion there is like, you know, there was some research that came out, I think a few months ago that they had found, they were able to sort of outperform some specialized time series modeling models with Transformers. And like, you know, I think there's really interesting stuff. You know, there's a story about Tesla removing 300,000 lines of code with a neural network. And, you know, I've just kind of got these bits and pieces. And one of the ways I work generally is like, when I have an idea of something to write or think about, I'll start a thread in chat, GBT or Claude, and I'll then save that somewhere. And then I'll just kind of keep coming back to it when I have more ideas. It's like, oh, here's another example of Transformers doing something. And so one of these conversations is actually that thing from, you know, probably four or five months ago when that kind of idea initially came into my head, maybe when I saw the research about time series modeling or something. Really interesting. Okay. Okay, so let's keep going. So you've got the sub-agent. And I actually, I wanna like just, actually I wanna pause on that real quick, which is, I think this is a very common complaint that they just dive in, and it's a common pattern to make a thinking agent. And I think Claude Code or Claude in general is probably the best one for this. So this is a thing that we faced with one of the apps that we've incubated called Spiral, which is a agentic ghostwriter. And I think we found, I found the same kind of thing when I was thinking about, okay, how does a good ghostwriter work? They don't just like, you don't say, hey, I want you to write a blog post, and they're just like, cool, I made it, here it is. Like a good ghostwriter is gonna get to know you and really understand, you're gonna work together to figure out what's in your head about it, but also shape what's in your head. Like it's not just, oh, I can see it and like they need to get it out of you. Like you're actually making it together. And in order to do that, you have to have a really good basic interview process to uncover things. And that sounds like you've found that too. And I think that's really, really interesting and really important for people who are thinking about how do I get the best out of AI? Actually stop for a second and like let it, ask it to understand you first. Yeah. One of the things I say to a lot of people is just like, I think partially because we call it generative, there's entirely too much focus on its ability to write and not enough focus on its ability to read. And it's like, its ability to read is incredible, right? And I think, arguably sort of like much more useful on a day-to-day basis. Like we produce artifacts far less frequently than we just like think about things. And so, yeah, I do this a lot. This is definitely a complaint I have about all the models is like, even when you very specifically tell it not to try to do your work, it still often still tries to do your work. And so you have to like really, really be like, no, I said no. Like I think actually if we look at, so here, critical. When Noah says he's just collecting source materials or I do not under any circumstances want you to try to write it, take this literally. Do not create outlines, drafts or any versions of talks slash writing. Only gather and organize the requested materials. It's so good. I love it. Yeah, this is like, but yeah, I think, I think we all experience that. And I mean, I do hope over time that that sort of gets baked into the models. I think it's a very interesting tension that exists with the model companies. Cause like obviously, like the sort of a lot of the economic output is sort of measured in the artifacts that it produces. And so I think it's very oriented and I suspect that part of it is just like that sort of the helpful assistant thing has like come to be a sort of meme that is probably self ingested. But yeah, it's, I think for those of us who are trying to do more interesting things with these models, it becomes a real barrier to work. Totally. Okay, so I wanna think about when you're using the thinking agent, did you say it like, is it outputting some sort of summary of what you've come to into a particular place or? Yeah, so that thinking agent is sort of told to, as it asks me questions, kind of make notes about the questions that it's asking me and keep a kind of running log of what I'm uncovering and how I'm thinking about it and all those sorts of things. Got it. And then, you know, you come back the next day and you're like, oh, I just wanna go down this rabbit hole on X, Y, Z thing about the, you know, this wild bill guy. And that you start in a new chat, maybe with it, maybe with the subdivision, maybe not. And that becomes its own new file on that topic. Yeah, exactly. So like, the wild bill stuff started as like deep research in chat GPT, and I, you know, had it go out and I'm reading the wild bill book right now. There's like one sort of particularly famous biography of him and, you know, I'm kind of thinking about the bits and pieces and trying to make, and I think I made a kind of interesting connection in there where, you know, a big part of what sort of he seems to have been after with the OSS and, you know, the sort of inspiration for the special forces was like empowering individuals. You know, that's sort of like the theme of that manual was like obviously empowering citizen saboteurs, but also, you know, I think a big part of the special forces is like, you know, having kind of like incredible operators at the edge who, you know, obviously operate within a sort of command and control hierarchy, but like have a ton of autonomy to move and execute independently because they're kind of, they have all the things that they need. And so, you know, in all of that wild bill research, I kind of went back to this and I was like, is this like an interesting way to connect all these ideas that like maybe kind of there's a, you know, and again, this is still early. I have not like solidified these conclusions as like, you know, the regular kind of writing process. Right. But it's like, well, I think there's this idea that like, you know, fundamentally, well, I know, you know, fundamentally one of the big things with Transformers is it moved us from sequential based models to models that can act in, you know, sort of paralyze their work better. And that obviously allowed us to have much more powerful and, you know, interesting models and has, you know, arguably kicked off this entire sort of revolution of what's going on and, you know, what we both do for a living. And so, you know, I think there's this kind of interesting connection. And so that was what I was playing with. I think here was like, oh, maybe there's this connection between kind of sequential processing to this kind of parallel. And then there's this connection to bureaucracy. And then there's this connection to Wild Bill who seems to be, have been very much about sort of like working within a system, but like having autonomy at the edges. And so that's kind of what I was playing with and just kind of taking notes. And then, yeah, I would jump out and be like, oh, well, actually I haven't figured out a conclusion yet. Let me start the conclusion section and I'll just sort of get that going on the side. But, and then, you know, I have a job so I can't be doing this all the time. So it's also like you interrupt yourself and it's really nice to be able to come back and be like, you know, can you catch me up on the last three days of research? Ooh, I love that question. That's so cool. And so, yeah, you can just kind of go in and be like, can you catch me up on the last few days of research? And it's just going to go read all this stuff, right? And again, it's like, I think the point you made earlier about the, you know, go find relevant sources. It's like, I find a lot that the difference between the people are getting a lot of this right now is part of it is just like, you have a good feel for where the edges of the capabilities of these models are. And you sort of like encourage them to work within those capabilities. Like this is an incredibly easy, you know, it's like, we know what it's going to do here, right? Like I could write all these Unix commands. It's just going to go find a bunch of files in this directory, and it's going to look at them by date, and it's going to look at all the files created in that project over the last, you know, and we know it's going to be able to do that. And so it's saying, you know, the major breakthrough day was this idea of bureaucracy as positional encoding, which is very much a work in progress idea, but I kind of like it. But, you know, so it's just like, it's pretty amazing also to just be able to kind of revisit deep work like this, right? Where, you know, you're going to break your flow. And it's like, it's often, you know, I find whether it's code or writing, the hardest part is like just picking it up again because you're out of it. And so just to kind of like kickstart that process is sort of amazing. I think what I was playing with here is this idea that bureaucracy was actually. um, bureaucracy was actually like an innovation, right? Um, that like, we look at bureaucracy as a negative, and generally, we talk about it as a negative, and I think often is a negative. Um, but you know, um, bureaucracy was a sort of like huge innovation for how companies operate, right? And ultimately, it sort of represents kind of hierarchy and structure, and a whole bunch of things that are like, actually like pretty positive for operating at a large scale. Um, and so, um, you know, again, my kind of whole thesis on AI around all this bureaucracy stuff is that what's interesting about it is that, um, as opposed to kind of past technologies, which kind of forced you to make a decision about whether you wanted to kind of like, use your existing sort of structure, and build that technology into your existing structure or adopt the new structure. Most of the time, the new software required you adopted the new structure. And that's why so many sort of software projects failed for so long, at least sort of part of what I think. And, um, you know, I think part of what's interesting about AI, what I find so interesting is like, that you can kind of keep letting everybody work in whatever way they want. You know, it's like a classic problem inside large companies is like, one team wants to use Asana, and one wants to use Jira, and one wants to use Linear, right? And so then at some point, there's like a, there's a, there's a huge project, and they bring in some big consulting firm, and they decide they're going to all centralize on this one thing. And now two thirds of the company is unhappy. And like, they've all made sacrifices. And you know, you're sort of in this like, very non ideal state. And I think what's really interesting about AI, and I, this is a little more sort of theoretical, because I think, you know, we're so early in this, is that like, I think it's very possible, you could just say, well, everybody just keep doing what you're doing, we're gonna stick sort of some models in the middle, they don't care what you use, because like, it's all just data structures to them. And so we can then have this sort of central thing. And if you know, I went, we talked about Percolate at the beginning, Percolate was a kind of marketing platform worked with very large companies. So it's an enterprise software product. And it's like, you know, at the end of the day, this is sort of the fundamental challenge of enterprise software is about like, you know, adoption and change management. I just think, I think, and I hope, and again, this is sort of the optimist in me that like AI kind of lets us just not worry so much about these things. And rather than trying to make everybody change the ways that they work, kind of let them work in these ways and let AI sort of, it's my I call it my Thomas's English muffin theory of AI, which is that it like gets into the nooks and crannies. And so yeah, that's the so anyway, but I have no idea what bureaucracy is positional and coding means yet. I'm hoping I figure it out in the next two weeks before I have to give this talk. I think no, but I think the point you just made is is totally right. And it's actually not, it doesn't have to be theoretical. Like, I've been seeing this too, inside of every and I've been meaning to write about it. And the place that it's been coming up is we have. So inside of every, we run like six different products. And we have 15 people. So it's, it's like a crazy product to headcount ratio. And what's interesting is, I really like doing things in a bottom up way. So everyone, each of the products has its own stack, we're not like centralized into a particular stack. Each, you know, GM that runs a product, like just has made a decision about do I run rails or TypeScript or whatever. And what I'm seeing happen, which is very cool, is a lot of the different products are running into similar things they want to solve for. So an easy example is, we have one product called sparkle, which is a little bit like a finder replacement or spotlight replacement. So it organizes your files, and then it implements really fast spotlight search. I'm a user. I like it. Okay, so then you know, um, and so that's really cool. And agentic search coming soon. Check it out. And, and we're just building a new product, new GM new stack called para, which is essentially an in house counsel. So it's short for paralegal, not para, like, you know, Tiago Forte para. And the whole job for para is just, you know, take all of your legal files. And whenever I have a question and be like, Okay, do we ever sign this contract? Or what's the employee agreement template or whatever, it just gives you the answer. And it's just a cloud code sitting on top of the directory. And, and a thing that we need to implement for that is this sort of like fast file file search. And what's really interesting is historically, if we wanted to reuse the stuff that we learned from implementing sparkles file search, that would have to be abstracted out into this modular library that anyone can use. And then we have to be on the same platform and like that, all those things, right. And what we did instead is, we just added Preeti, who's the developer for, for para right now, we just added her to the sparkle repo. And I was just like, just ask cloud code to figure out how it works and just do your own version. And so you get this like sort of tacit code sharing, where we all get better, but without having to do the work of abstracting and modularizing everything, because the percentage of things that you can do that for are pretty low, because it's a heavy lift. And I'm seeing that happen all the time, we're just having a bunch of repos that are all solving similar problems, but in different environments in different ways, you, everyone gets more productive, because AI can kind of translate. I've, one thing we've done there, we also, so at Alephic, we do a whole bunch of building for very large brands. And so we sort of build all kinds of AI things. And, you know, so we've got lots of sort of internal and external repos, and we frequently have the same thing. And actually, I've used the GitHub MCP a few times for that same purpose, which is just like, you know, you're just in cursor cloud code or whatever. And you're like, Hey, can you go like look up, we run it, we've got an internal tool called intelligence that just sort of is a wrapper around a whole bunch of like, stuff that we use, right. So it's like got some CRM stuff. And it's just like been a fun place to build the things that we need to run our company. But it's also a good place to kind of experiment and explore and figure out solutions to interesting problems. And so I'll frequently be like, Oh, can you go to like just go look at the intelligence repo. And, you know, look at how I implemented that thing there, and take those sort of best practices and just pull them over. And yeah, I think that stuff, again, that's where I really do believe in this idea. I like one of my whenever we have like a client meeting or something, my first the question the icebreaker I always use is what was your aha moment with AI. And mine was I mean, it was probably not the very first, but it's the one that sort of I think was most impactful was I was I got access to build a chat GPT plugin room and plugins came out and like two and a half years ago or something now. You mean 50 years ago? 50 years ago. And, you know, I like you, I've written a lot of software in my life. And I you know, you know what you do when you like get access to something new. It's like, I've got to go read the API docs and figure it out. And you know, like, there's a going to be a contract. And you know, as long as you follow that contract, it works. And I go read the plugin spec. And it basically is like, oh, you just stick a manifest JSON file in the root directory of your application. And in that you describe how you want us to send you data and you describe how you're going to send it back to us. And then we'll deal with the rest. And I was just like, that's amazing. It's also like it's how the world should work. Like I wish everything worked that way. I wish I didn't always have to adhere to the big company's contract for how to send and receive data. But also like I the thing that really struck me in that moment, and it's like been my kind of like rallying cry around all this stuff is that it's also just like fundamentally counterintuitive in that like, I literally have a career's worth of intuition for how to integrate software systems. And it flipped it on its head, like, like, like quite literally 180 degrees away from my intuition of how software systems should be integrated was this thing. And that I think since then has been my kind of thing for everybody has been like, this is just not intuitive for now. And and that's not a bad thing. It just means like, you need to build intuition. And like, that's what we're all just out there trying to do with it. Right. And so, you know, when I don't know, I mean, part of what I like about what you're doing. And, you know, even just hearing the things you're saying, but like, generally, what you do with the podcast, and what you do with every is like, so much of it is like, we're all kind of just figuring stuff out for the first time, right? And like, um, you know, we're like, Oh, will this work? And then like, all of a sudden, you have this new bit of intuition for what these things can do, and what a computer that is not deterministic looks like. And that's, I think that's just what we're all doing all the time. And that's why it's so fun. I think that's why I love this moment. Because like, you just have a weird idea. And you're like, has anyone done this before? And, and it's like, No, and it's not, it's not a complicated idea. It's just, it's just a new whole new territory, you know? I Yes, I think about that all the time. And I think actually, like, I think one of the really damaging sort of things out there is that, um, I think there are a lot of people who think we're way further along in this than we are. And so, you know, I think particularly the people who are sort of scared, you know, we run, we work with like fortune 50 companies. And so, you know, when we're sort of like, out there, and we're talking to people inside the organization, a lot of people feel like they've already been left behind. And it's like, no, you can like literally go sign into chat GPT. And like, had do something like nobody's thought about doing with this thing yet, because there's just so much white space to explore. And you might discover some totally new way of using it and or like totally new trick. And I don't know, that's just, that's, and, you know, I think, to be fair to some people, that's sort of very intimidating. And I don't think, by and large, the models do any favors to themselves and helping those people get their feet wet. In that, like, you know, I think people go on there and they, you know, it's like, you ask it to write you a poem, and then it writes you a poem, you're like, Okay, it wrote me a poem. But I don't know that feeling of like, that feeling of Yeah, it's like being on the frontier, right? Totally. And yeah, I think that your point about intuitions and getting intuitions is the big thing. And I think people, we don't realize is when you're dealing with something fundamentally new, you, you can't trust, like how you reason about it without experiencing it, because you have to build the intuition in order to be able to reason about what it means and how it fits in and whether it works or not. And we're just not used to that, because we're used to reasoning about things we already have an intuition for. And, and I think that's why, like, when you first see, maybe when you first start chatting to be like, Oh, my God, it can do everything. Like, we're not gonna have jobs in a year. And now we're like three years in, and we're like, yeah, it's awesome. And jobs are complicated. There's a lot of complex stuff that we do, you know. And I love I love kind of that, you know, in order to build the intuition, all you have to do is use it and that just by using it, you're already kind of on the edge for now. And yeah, I think that's the best there's apparently there's a German word called finger spitzengefühl. Of course, there is building fingertip feeling. And that's been my just because I can't resist. Also, I in that whole in in sort of the realm that you're discussing, like, I have been trying to do a lot of analogy analogizing, right? It's sort of like, and I think, you know, that's really hard. And, you know, but my two that have sort of stuck the most one is just, I watch a lot of YouTube with my kids. And we watch this channel called Veritasium. It's a science channel. And I love Veritasium. Yeah, it's great. And he did one where he built a bike that locks out left if you try to turn right and locks out right if you try to turn left. And what he's proving is that you can't actually turn a bike left unless you can turn it right. Which none of us would think about when we ride a bike because it's all just second nature and intuition. But it's also why you can't explain to a child how to ride a bike. They just have to get on it and feel it. And, and so you know, I really that video is amazing. And it's that channel is amazing. And and but I thought a lot about that. And then the other one, which is a sort of deeper cut is there's an amazing book about quantum physics called Beyond Weird, by Philip Ball. And the thesis of the book is basically that like, there's nothing particularly strange about quantum physics that we like, we have a very good understanding of it, like, we wouldn't be talking right now, we wouldn't be on computers, we wouldn't have phones, if we didn't have like a very good grasp of the mechanics that exist underneath it. And his thesis in the book, essentially, is that like, what's really lacking is the vocabulary, because like, we all exist in a Newtonian world, not in a quantum one. And so we all have words that reflect the sort of deterministic processes of that macro universe. And I think a lot about that I have not like fully been able to sort of pull that string all the way to AI. But I feel like there's a real connection there. Because I think that there's just something really weird about using probabilistic computers, like we're not used to using things that, like you asked them the same question twice, and they have different answers. Like, that's very strange. We're not used to I'm not used to writing code where you can tell the larger company how you want them to send you data, and they can just do it like these are not normal things that any of us have lived with in our lifetimes. And so of course, it takes some time for us to adjust. I think so too. And I actually have a hope that language models by becoming a standard way that we use computers will create that vocabulary. Because we actually are quite good at dealing with probabilistic non deterministic things like other humans. We've just grown up in a world where, because of, you know, the Enlightenment and the scientific revolution, and, and the tools that came out of that are very much like deterministic. We've associated that with how we see it, like that's how we see the world because of those tools in that language. And there's a whole other part of the way that we see the world, which is much more squishy and much more like vibes based that has been, I think, deep, deep prioritized, especially in Western culture, that now that we have a tool that works that way, I think we'll be able to start seeing that again. And that's one of the beautiful things to me about language models is it opens up that whole world again. Yes, I love it. I do want to go back to cloud code. And we should do the phone unless there's unless there are other things that you that you want to share on the computer. But the the thing I want to do before we get there, that's just on my mind right now is like, you said, you said, you know, you watch this with your kids. And I'm sort of curious, how, like, what do your kids think about this? And how are you dealing with it with your kids? Yeah, I love that question. So I've got a seven and a 10 year old. And obviously, like, I'm pretty kind of deeply embedded in this stuff. And so I've sort of exposed them quite a bit to it. You know, they don't. So they will like occasionally use the sort of voice models and they have a pretty good understanding and we'll be in the car and just play games and ask questions with Grok and do those kinds of things. This weekend actually, for the first time, my 10 year old, she was really eager to be every year. My wife and her sister and brother and mom and all the cousins, we all get together and we do Christmas together. And so it's too many presents to give to everybody. So we do a kind of like not secret, secret Santa where everybody chooses one person. And my 10 year old really wanted to be the one who got to be the chooser. And I encouraged her to vibe code an app to do it. And so I just gave her my phone and V zero. And honestly, that was like so amazing to watch. Like not just cause it was so cool to see her do that and build it. And she went through, she was having so much fun. She did 75 revs on V zero. So she like really got it going. Polished Santa app. She also like started to get into like really interesting kind of like computer science ideas without knowing it. So in one of the things like the adults give presents to adults and the kids give presents to kids, but she wanted this to be a more generalized app. So she realized that like rather than having adults and kids, you need to call them groups. Right. And like, you know, so she's like getting into data modeling and like all of this, I'm like watching this conversation happen. And I just thought that was so awesome. And, you know, also just like a real pet beam of mine right now. And I've sort of gotten this argument with a bunch of people is like, there seems to be a big conversation that like, there's a bubble in vibe coding and like, because one company or another might have too high of a valuation. And my take on that is like, I just, I could not care less what the valuations of these companies are. I think like fundamentally, if there's a tool that can allow a 10 year old to like build an app, there can't, that can't be a bubble. Like I just like can't see a possibility where that is that. So anyway, that's sort of one side of it. The other big one for me that I've been thinking a lot about is sort of media literacy and education stuff. So, you know, both at the sort of schools they go to, and then also I went to NYU and I've sort of been having more and more conversations with the Dean of the school I went to there. And there's a lot of fear inside schools right now about AI and about cheating. And there's a big thing, you know, so some parents in my town, they, you know, they wanted to have more of a conversation about it and, you know, as someone who, I've thought about this a lot, but I've also just like been, I've spent my entire life thinking about sort of technology and its effects on culture. And I think I'm like relatively grounded in these things. I've like, I've put in good hours of thinking. I mean, I know that for sure. And so, you know, my take on it is like one that sort of, you can't hide technology that won't be hidden, right? So it's like, you know, putting our head in the sand is not the best solution. And then, you know, my bigger one though is like, I was out, a friend of mine asked me to come talk to a school two years ago about AI out in LA. And afterwards I was talking to an English teacher there and she was like, what do I do? Like, what do I do about all these kids, you know, using AI? And I was like, look, I don't really know what your job is because like, I mean, being an English teacher for 11th graders sounds really much harder than my job. But on a really fundamental level, I don't actually think your job is to teach these kids to write, because that's like a lifelong pursuit. I think your job is to convince them that it's worth learning to write. And so in that way, like, I'm not sure that anything fundamentally changes because of AI. Like, I think that, you know, and again, this is my very optimistic take, but like I am, I think that there are so many parts of the education system that AI really just exposes the sort of flaws in the way that we teach. Like, why are there so many tests on these kinds of things instead of encouraging thinking and learning and coming to love to write and research and whatever? You know, it's like, we're so focused on teaching kids the, you know, five paragraph essay, you know, while every adult who is a writer has long abandoned that. And because like, it's all about sort of discovering that you like to write and you, you know, what your own style is and how to do it. And, you know, it's like, I'm sure it's like, you know, a big part of working with AI to write is like telling it, is ignoring it. Cause you're like, no, that's not me. I'm not into that. Like, I'm totally comfortable saying really here. I know you don't think it's a good idea, but like, I'm cool with it. And so, you know, I don't know. I've been sort of having a lot of these different thoughts. I'm actually pitching a class for the fall of 26 at NYU to kind of, the idea for it is code as essay. And my sort of point of view is like, this sort of opens up this new way to express yourself. And that, you know, like we have all these other ways that we celebrate to express ourselves, but code has been like long shut off from people because it's, but actually it's kind of amazing. And it lets you express yourself in all these different kinds of ways. And like, you know, this is what my 10 year old was doing this weekend. So anyway, those are all the bits and pieces as a parent. I've been thinking about the one other thing I will plug is media literacy. I think is a big piece of it. A lot of people are afraid of these models and hallucinations. And there's a book by a guy named Tim Harford who writes for the FT and he's an economist. And he has a book called The Truth Detective, which is an adaptation of The Data Detective, but it's written for kids. And it's the best media literacy book I've ever read for adults or for children. And I think, you know, a lot of what this AI conversation exposes is like how bad a job we do with helping and arming our kids and our adults to be sort of like truly media and technology literate. And, you know, like being really good at knowing what's real on social media turns out to be also really useful for like differentiated between hallucinations and non-hallucinations in tragedy BD, right? Like this is a sort of, to me, a kind of very central skill that like we need to arm everybody with. And I am sort of way more interested in that with my kids than I am in worrying about them cheap. That was a very long answer to your question. I don't know if it got at what you were looking for. No, it's amazing. That's exactly what I'm looking for. And it's sort of what it strikes me, another way to frame what you're saying is, for example, rather than having them memorize and be quizzed on the 50, what the 50 states are, asking them to go find the 50 states, which had to be T and be able to tell when the AI is giving them the wrong answer, because that's a lot more of the meta skill that they're gonna need anyway down the line. And again, I'm not a teacher. I'm sure there's lots of teachers who were like, this is, that's crazy for a lot of probably good reasons, but there's something interesting there where it becomes the meta skills become more important than they used to be. And in order to do well at the meta school, you have to also be able to like, to some degree, do the underlying skill too, but we probably could be spending much more time in the meta school than we are now in the education system, like isn't really set up to do that anyway. Yeah, and I think even simpler examples is like, I went to a school called Gallatin at NYU and when you graduate, you have to sort of, it's not quite a thesis defense, but you have to sort of spend three hours with four professors and, or three professors and sort of explain kind of your line of reasoning around why you studied what you studied. And you need to be prepared to kind of like, weave into that defense, any of 25 books that you put on your book list. And I was talking to them and it's like amazing. That's like entirely AI proof, right? Like there's no cheating on that. Like you show up in that room and you're either prepared to speak to it or you're not. And whether you're prepared with AI or not it doesn't mean anything, right? Like, it's like, do you, can you, can you make up an argument in this room? And like, not everything is going to be that easy to be sort of like cut off, but like, I don't know, there's something really beautiful about that idea, right? Because it's like, it's naturally cheating proof because like you're sitting there and it's a question of like, did you actually internalize these things? And I don't know, that's way more interesting to me than even like, was your essay good or any of these other, it's like, did you, did you get it? Like, and so yeah, I don't know. I'm trying to do my best to kind of like take a balanced approach and try to at least sort of like tamp down some of, I live in a small town in Connecticut and I think there's a lot of fear amongst parents. It's like, it was mobile phones and then it was social media and now it's AI and it's like another thing that's going to ruin our kids. And I don't think that that is true, but I think there are things we can and should do to encourage it to not be true, like really get them really good at the things you're saying like, how do you tell? And again, it's like a hallucination is just a form of the same kind of misinformation that exists in on television and on the internet and in social media and everywhere else. And, you know, just sort of like encouraging people to kind of get in touch. There's a great part of the truth detective for the kid's book, he calls it the brain guard. And like one of the bits of advice he has is when you encounter some piece of information, if it makes you feel really good, cause you agree with it, then you should be even more skeptical of it. And he calls it the brain guard. You know, and he's explaining this, like this is for a nine-year-old. And I just thought that was like such a beautiful way to put it, right? Like, that's like what you learn to do when you get good at being on the internet is that you're like, wait, I should like be more skeptical of this because this is like in line with everything. I think, let me just double check the way, like I, you know, you get to learn that feeling in your gut and get to learn when to react to it. And so, yeah, that's a lot of how I think about it. That's great. I'm interested. I'm gonna get that book. I'm interested in reading it. You should. My plan is to read it to my kids every year from now on. Nice. I love it. Just refresh it. All right. Now, for the moment we've all been waiting for, show us how you use Cloud Code on your phone as a second brain note taker. Okay. So here we go. So I am going into an app called Termius. Termius is just a terminal. And what is allowing all this to happen behind the scenes is in my basement, I have a mini PC. And on that mini PC, I have a thing called tail scale running. And tail scale lets you set up these very simple VPNs. So I'm currently inside, like if I scroll down here, you see I'm on a VPN. That's my personal VPN. I'm not like on an outside VPN. I see. So the only way to access this machine is through my VPN. Okay. And so then when I go in there, because I sync my Obsidian with Git, so I put it, it's on GitHub, in a private GitHub. I can then sync it back down to here. And so then I can just call up Cloud. And now I'm just in Cloud Code talking and thinking, and I can just be like, what's new in the last two days? I can access any of my agents. I can do anything. And again, this is in my Obsidian, but I can use this anywhere, right? So I'll be like on the fly. I've got other repos in here. You know, I realized like a link was broken on my conference site. And so I just opened the repo. I pulled it down. I asked Cloud Code to make the changes and I was able to do it right here. So this has been like completely wild to me, because again, this is very much in that like, like on Tuesday of this week, we had Monday off, Tuesday I dropped the kids off at the bus, and then I went and I sat and had breakfast. And I literally sat on my phone and worked on this talk for like two hours. And I did it through here, right? Like on my phone, where I was like doing real thinking and research and pulling things in and pasting things in and doing all this kinds of stuff. And, you know, I'm able to do it all. And it just, it doesn't seem like I could do that kind of thing without that. So yeah, this has been like a completely revolutionary change in my life. And actually one of the things I've been doing lately is like setting up. I've got all these friends now who I've set up like little partitions of this mini PC in my basement so that they can also run cloud code on their phone because I like it so much. Does this make you be like, oh my God, I got to drop everything and just build a actual purpose-built notes app that has cloud code as a backend for this? No, I mean, actually one of the things I've been thinking a lot is like, maybe I just like, everything should just run in Linux all the time for me. Maybe this is like, at least for the short term, this is the answer to all of what I just need to like not have anything anywhere else. No, I mean, I will say I'm sort of pretty out of the SAS game these days. So I don't often kind of think that I should drop everything and do anything. I find this to be a really amazing solution. But no, I mean, but this has really, this has really like changed the way I work. And I feel like I can just be anywhere and just be on my phone. And, you know, I mean, I was out, like I needed a break. It was, you know, 4.30. I went and sat outside for a while. And then we had a project that needed to get delivered to a client and a small change needed to be made that like I was the best suited to make that change. And so I just like hopped on my phone. I pulled the repo down and I went into cloud code. It's like a tiny little change. You know, like the way I find myself using cloud code the most for code is that like mostly I'm having to do the work I already know how to do. You know, I'm like, oh, I like, I knew exactly what was going on in that situation. Like I knew why we were having the issue we were having. And so it was like, I could have gone back to my computer and opened up a cursor and done it in cursor either by hand or with cursor. But it was like, I just, I was like, I told cloud code exactly where to look. It was like, and I first confirmed that the problem was what I thought the problem was. And then I just had it push a solution and it pushed a PR and then I was done. Amazing. And I was still sitting outside by the pond. I love that. Yeah, I've definitely had that experience. I've never, I've not done it on my phone. I'm like, I have my laptop out with me, you know, by the pond or by a lake or whatever, but you're inspiring me. I have a Mac mini in the office that I've been meaning to set up. So I think this is gonna be good. One of the other, by the way, one of my other, I'll just take you out of here for one sec, actually, just to show you this. One of my other big ahas recently has been building Claude code helpers for doing basically basically like setup work. So it's like, I'm not, I'm like been playing with Linux lately. I'm playing with this Omarchi, which is DHH's Linux distribution. And I'm not like super comfortable in here. And so I got this whole, this is a cloud code project specifically to help me configure this box. And it's like so nice. Cause I'm like, oh, how do you do this in Linux again? Or like, what's the NeoVim command? Or like, can you change this? Can you help me install this plugin for NeoVim or whatever it is? Or, and so now I have one on my Mac too, where it's like, can you clean up all the homebrew things? Or like I switched from like which Python package manager I was using. And it was like, that would have been super overwhelming for me. And I was like, I want to switch from using pip to using UV. Can you like just make that happen? And it like just did all this stuff for me. And it knows all my preferred settings. And so I actually have a version of this where like now I've got it so tuned that if I want to launch a new box for doing something, it'll just have all my settings ready to go. And then I can log into Cloud Code and the Cloud Code can then set up anything else that didn't get set up in the initial process. That is amazing. That's wild. This is my happy place. I can see that. Are you, do you have any like, are there any big projects like this that you've been itching to do or itching to try out? No, not really. I mean, I've been having a ton of fun. My server stuff has been a ton of fun. I've been doing a lot of that. I'm, like I said, I mean, this is kind of a joke and kind of not, it's like, I'm super interested in like doing more, because Cloud Code has become such a sort of integral part of my life. Like I'm very interested in the command line. I found myself installing more and more things into the command line and like doing more and more work. So I've been using like, Simon Wilson has a LLM command line tool and like doing more and more stuff sort of in that. And then like also layering that back into Cloud Code. So it's like I did my newest Cloud Code little Obsidian tool is it, I have an attachments folder in Obsidian where all the PDFs and images and stuff in any note go. But inevitably they have terrible names, right? I mean, and so this goes through very similar to Sparkle. And, but just in that Obsidian folder and it renames them all. And then it also puts them in like a metadata. It puts them in a table in the attachments folder and then it renames all the attachment links back. So just like cleans everything up. It just does it through Gemini Flash. And so it's like, I don't know, stuff like that's kind of amazing. So I don't know, I'm just like, I'm having the time of my life just building and tinkering. And, you know, I mean, this is just on the side and I get to do the same thing. I mean, we work with like Amazon and Meta and PayPal and all these big companies and, you know, we're just like building amazing stuff all the time. I love that. I love the energy. If people are interested in following you or working with you at Alephic, where should they find you? Yeah. So Alephic is alephic.com, A-L-E-P-H-I-C.com. And then I also run this thing called brand, brxnd.ai to make it particularly confusing. That's a conference. We've got the conference coming up on September 18th in New York City. You should come if you're around, it'll be really fun. We're going to talk about marketing and AI. And I also write a newsletter there at newsletter.brxnd.ai about sort of specifically at this intersection of AI and marketing. Those are kind of the best places to find me these days. Awesome. Noah, always a pleasure. Pleasure's all mine. Thank you, Dan. Oh my gosh, folks. You absolutely, positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. It's like finding a treasure chest in your backyard, but instead of gold, it's filled with pure unadulterated knowledge bombs about chat GPT. Every episode is a rollercoaster of emotions, insights, and laughter that will make you feel like you're on a rollercoaster. And if you want to learn more about AI and I, it's filled with pure 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. 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