[0:00]This is Obsidian, and Obsidian is this little tool that people are using as their second brain. But what's really cool about it is they're pairing it with Cloud Code, and they're getting crazy results out of it. It's literally a game changer. Now, I've been slow to adopt Obsidian because to me, it's been a little daunting to look at. So I had my friend Vin, and he clearly explains what Obsidian is, how to use it with Cloud Code, how to set up these commands that really drive the most out of Cloud and all the LLMs. And it's an incredible episode, like a really game-changing episode, because I think that people who understand how to use Obsidian and how to use Cloud Code together, they're going to be able to live happier, healthier, and wealthier lives. Why? Because it gives incredible ideas to you on tap. So I know that the people that stick around to the end of this episode, I think that for a lot of them, it's going to absolutely change how they use AI, and it's going to be a super impactful way because you're going to get better ideas at the right time, the right moment, and it's going to make you happier, healthier, and wealthier. Enjoy the episode.
[1:21]I've got my dear friend Vin, also known as internet Vin on the podcast. I literally begged him to come on. I begged him. I begged this man to come on and to teach us a very specific thing. Vin, by the end of this podcast episode, what are people going to learn? I want you to have an understanding of how you can use Cloud Code and Obsidian as a thinking partner. I want you to have an understanding of how you can stop having to explain things to agents over and over again and just pass specific files in. And I want you to understand how you can use Obsidian Cloud Code to notice things about the way you think that you would not have noticed on your own without these tools. All right, from your lips to God's ears, let's get into it. Okay, so first is like, what is Claude Code? So Claude Code is this like agent that you can use in a command line interface. So it's just basically this tool you can use that can control your computer and you can use it through natural language, right? So I can say, make a file or make a file on my desktop that says hello Greg in plaintext, right? And it's going to go and do this. That's really cool. That's that's something that's that's new. That wasn't possible before. Before this, I had to go to the desktop, open some text editor and then like create that file, right? And now this file is on my desktop. So I can say open the file.
[2:59]There we go. Hello, Greg, that's crazy. Right? Um, now what's interesting about this is if you have this agent that can like control and do things on your computer, that means that whatever you can describe to it, like it can start to do. And so when you if you describe a project to it or you get into these long conversations with an agent, um, it can do more and more complex things. The more information it has, the more complex things it can do, but the problem is that if you have to, let's say, you know, like I write some super long description about a particular project or I have like an hour conversation with this agent about a particular project, it's like I don't want to have to create a new session to explain that all I don't want to have to explain that over and over and over again. Um, a lot of people are using like Claude or chat GPT on the web, and it has things like memory, but you you can't like control, you don't know what's in that memory, right? You don't know what it knows and what it doesn't know. And so there needs to be some way of like, you know, passing information into these agents that is easier and faster. And the better information you can give it, and the faster the information you can give it, the more stuff if it can do for you and the better, the faster you can delegate to it. Okay. So now, even if I, let's say, let's say I had like, you know, let's say I wrote like a big project description here, right? Create a file that describes, you know, a project, um, about a to-do list app that is very minimally designed and reads from all of my calendar and messages and slack and interprets into a task list that of tasks that it thinks that I should do.
[4:57]I don't know, some some idea, right? So now, this this is a file that could be on my desktop, and what I can do when I use Cloud Code is I can reference that file and pass it in whenever I want. And why that's important is because it's the context, right? The whole game is feeding the beast good context. Yes, exactly. And I don't want to have to do this over and over again, and and and when I work on this, uh, over days, I I'm not going to remember like what we talked about, right? So I want some kind of file, uh, that I can like pass in. Oh, sorry, Greg, one second. Yeah, and that's that's sort of the problem that a lot of people are facing with Claude Code is like they're using it and then they're saying, well, it's it's okay, it's not like game changing. And the issue is they don't have they're not they're not feeding the right context at the right time. Yes, exactly. And so here's, so here's like a a project description that it wrote and obviously I can pass this in, and this is like a this is like a general one that I just created, but you you can make these like very complex, you can build them into like robust files, right? Over time. So we know that, uh, Cloud Code can create files and it can repeat and it can, um, uh, read files, right? So now I can say, let's say I created a new session, so here's a new session, and then it's like I'm about to work on something, but before I work on it, I can just type context demo. Now, it's going to read a whole bunch of files about where I'm currently at, done. Like I've already pre-loaded, I've already pre-loaded in all this context now. So you can see it's going to start reading all these files. It's reading a read me, it's reading context about new, which is a media company that I'm working on. It's reading about other stuff, it's reading my personal workflow context, the other stuff is my show, it's reading the personal workflow context, and so I don't have to worry about it not knowing the key information that I wanted to know. I just did that one command, and now it's going to get all that information, done. So I can use slash today, which is a morning review, it pulls calendar, tasks, I messages, and the past week of daily notes into a prioritized plan for the day. Why does this matter? Well, okay, sure, you can set up an agent and give it access to your calendar and your tasks and I messages and things like that, but it's that that that doesn't have all of the information about what you're thinking about and why. If I'm writing daily notes about some particular technology or project or thing that I'm interested in, does my calendar reflect actively like, does it match the subjects I'm actually writing about? If an agent has that context, you can it can it can, uh, more effectively give you, um, information about what you should do or not do, or it can more effectively make decisions on what should be in your calendar or not in your calendar. Here's another one, slash close day.
[8:06]End of day processing, it extracts action items, surfaces vault connections, checks if confidence markers need updating. So I have a bunch of hypotheses that I I think about and I give them a confidence rating. This is an idea I'm working on, I feel very solid about it. Here's another idea I'm working on, I'm not sure about it. So these are like, um, daily operations things. But this is what I use Obsidian for the most, which is thinking tools.
[8:42]I really, really, really like working with LLMs as a thinking partner. That's my favorite way of using LLMs. I know people like to use agents and LLMs to build things, but I really like using them to think alongside me and build when I feel like, you know, I really have a novel way of viewing things.
[9:19]So let's see here, um, so Ghost, here's here's a command I have. It answers a question the way I would. It builds a voice profile from the vault, writes in that voice, then evaluates the fidelity. So I can just say, what do I think of AI? And I'm going to show you this. Challenge topic, it pressure tests current beliefs using the vault's own history, finds contradictions, counter-evidence, and shifts in thinking. Why does that matter? Well, if I want to make sure that I'm continually developing as a human being, and as a as a as in my skills, I want to make sure that, you know, the POV I have isn't overly biased or limited. So this can challenge me. Emerge, surfaces ideas the vault implies but never states, conclusions from scattered premises, unnamed patterns, unarticulated directions. This is super, super useful because a lot of times, you know, I I can be stuck just surfacing ideas in a in a in a lot of different ways, like for years. And just having someone say a simple thing to me that just says, hey, this is just naming the idea, hey, did you know that you keep circling around this pattern? Huge breakthroughs. Slash drift. It compares it compares my stated attention intentions against actual behavior over 30 to 60 days. Surfaces what I'm avoiding. Ideas. People on this podcast, the listeners will probably like this one. Deep 30-day vault scan with cross-domain pattern detection and graph analysis to generate ideas across all domains. This gives me, um, not just ideas on like things I should work on. Like it gives me ideas for tools and things like this, but it also gives me ideas on like films I should watch, products I should buy. Again, all influenced by like like things I'm writing about in my vault. Um, trace tracks how an idea has evolved over time across the vault. So let's see some of this stuff. The trace demo. So I did this one already, and the way this would work is I just like create a tab here, and I could just be like, Cloud Trace. And I had to create demo versions of all of these commands because of how much personal information is in my vault. But still, I don't even know like I I I can't even control what is going to show up on the screen, right? Um, but that's part of doing demos like this, which is which are kind of weird and interesting. But you can see personal agent infrastructure, it links to like Agenc AI, there's like a link here to Telegram. There's a link here to like Toby, the founder of Shopify. There's a link to like presence log, Cloudbot, you know, and then here's like, I I have a podcast too called the other stuff, and like you can see I'm obviously doing a lot of like thinking about that a lot, right? And so I can also, let's say if I go to Greg Heisenberg, and I go to local graph, so here's like all the times I've written about Greg Heisenberg, right? Notes on time constraints, how I use Obsidian, which is just kind of interesting. Um, so if I'm listening to his show, and I'm picking up different patterns, I can I can reference that back to to Greg. So that's really interesting. But here's the thing. The reason why people love Obsidian is because of these interrelationships. The idea that you could open a file, and then, you know, I just open this file, and then I'm like, oh, interesting, I mentioned Greg Heisenberg. I can click that and it goes to that file. That's interesting, right? It shows, it works more to it, uh, it works more like the way your brain works. Your brain connects these patterns all the time. Here's a, yeah, yeah. So I see why it's interesting, but how does this get me better output? Exactly, yeah. So the next thing is Obsidian released this new tool called Obsidian CLI, and what that allows you to do is it allows you to use Claude Code, and it can go, and it can read all of the files in your Obsidian vault, which is a folder of text files. But with the Obsidian CLI, it can give Claude Code not only those files that it can read and access, but it can also give Claude Code information about the interrelationships of those files. So you can see, so Claude Code can see that, oh, this file is connected to this file and this file and this file. That gets very interesting in terms of what Cloud Code can understand about you and what Cloud Code can understand about all of the relationships between the things that you're working on. It can start to surface patterns about what you're thinking about that you are not seeing for yourself. Some idea that you might have been writing about for a year in this vault, it could be a latent idea, and it can just immediately say like, hey, did you know that you've been writing about this same pattern in startups or in this particular project you're working on, and every single note you're making across these different domains? And and in seeing that for the first time can be like a huge light bulb effect. It can cause like huge progressions in your learning and your understanding and your point of view on the world, but also in what you're working on. Um, so I've written out, I wanted to demonstrate how that actually works in terms of how I can pass information into an agent that would be impossible without Obsidian and Claude Code. So here's some commands that I have that I use, and I don't want you to be afraid of like all this stuff. I know this can look intense, but, um, here here's what, here's what I've got, some commands, and this is just terminal that I've created, and I'm running it in Obsidian. You don't need to use this, you can just also do this in your own terminal session on in whatever tool you want. But I put it in Obsidian because I want to see it all together, and I wanted to show you the ways in which you can like integrate and customize this environment.
[15:24]So here's a cool thing, so context slash context, load full context about my life, work, and current state. Reads context files, daily notes, and follows backlinks to build a complete picture. So I'll just show you that right here.
[15:55]So like, let's say I open a new session in in Cloud, just on my desktop, and now it's like I'm about to work on something. But before I work on it, I can just type context demo. Now, it's going to read a whole bunch of files about where I'm currently at, done. Like I've already pre-loaded, I've already pre-loaded in all this context now, so you can see it's going to start reading all these files. It's reading a read me, it's reading context about new, which is a media company that I'm working on. It's reading about other stuff, it's reading my personal workflow context, the other stuff is my show, it's reading the personal workflow context, and so I don't have to worry about it not knowing the key information that I wanted to know. I just did that one command, and now it's going to get all that information, done. So I can use slash today, which is a morning review, it pulls calendar, tasks, I messages, and the past week of daily notes into a prioritized plan for the day. Why does this matter? Well, okay, sure, you can set up an agent and give it access to your calendar and your tasks and I messages and things like that, but it's that that that doesn't have all of the information about what you're thinking about and why. If I'm writing daily notes about some particular technology or project or thing that I'm interested in, does my calendar reflect actively like, does it match the subjects I'm actually writing about? If an agent has that context, you can it can it can, uh, more effectively give you, um, information about what you should do or not do, or it can more effectively make decisions on what should be in your calendar or not in your calendar.
[17:48]Here's another one, slash close day.
[17:55]End of day processing, it extracts action items, surfaces vault connections, checks if confidence markers need updating. So I have a bunch of hypotheses that I I think about and I give them a confidence rating. This is an idea I'm working on, I feel very solid about it. Here's another idea I'm working on, I'm not sure about it. So these are like, um, daily operations things. But this is what I use Obsidian for the most, which is thinking tools.
[18:32]I really, really, really like working with LLMs as a thinking partner. That's my favorite way of using LLMs. I know people like to use agents and LLMs to build things, but I really like using them to think alongside me and build when I feel like, you know, I really have a novel way of viewing things.
[19:09]So let's see here, um, so Ghost, here's here's a command I have. It answers a question the way I would. It builds a voice profile from the vault, writes in that voice, then evaluates the fidelity. So I can just say, what do I think of AI? And I'm going to show you this. Challenge topic, it pressure tests current beliefs using the vault's own history, finds contradictions, counter-evidence, and shifts in thinking. Why does that matter? Well, if I want to make sure that I'm continually developing as a human being, and as a as a as in my skills, I want to make sure that, you know, the POV I have isn't overly biased or limited. So this can challenge me. Emerge, surfaces ideas the vault implies but never states, conclusions from scattered premises, unnamed patterns, unarticulated directions. This is super, super useful because a lot of times, you know, I I can be stuck just surfacing ideas in a in a in a lot of different ways, like for years. And just having someone say a simple thing to me that just says, hey, this is just naming the idea, hey, did you know that you keep circling around this pattern? Huge breakthroughs. Slash drift. It compares it compares my stated attention intentions against actual behavior over 30 to 60 days. Surfaces what I'm avoiding. Ideas. People on this podcast, the listeners will probably like this one. Deep 30-day vault scan with cross-domain pattern detection and graph analysis to generate ideas across all domains. This gives me, um, not just ideas on like things I should work on. Like it gives me ideas for tools and things like this, but it also gives me ideas on like films I should watch, products I should buy. Again, all influenced by like like things I'm writing about in my vault.
[21:09]Um, trace tracks how an idea has evolved over time across the vault. So let's see some of this stuff. The trace demo. So I did this one already, and the way this would work is I just like create a tab here, and I could just be like, Cloud Trace. And I had to create demo versions of all of these commands because of how much personal information is in my vault. But still, I don't even know like I I I can't even control what is going to show up on the screen, right? Um, but that's part of doing demos like this, which is which are kind of weird and interesting. But you can see personal agent infrastructure, it links to like Agenc AI, there's like a link here to Telegram. There's a link here to like Toby, the founder of Shopify. There's a link to like presence log, Cloudbot, you know, and then here's like, I I have a podcast too called the other stuff, and like you can see I'm obviously doing a lot of like thinking about that a lot, right? And so I can also, let's say if I go to Greg Heisenberg, and I go to local graph, so here's like all the times I've written about Greg Heisenberg, right? Notes on time constraints, how I use Obsidian, which is just kind of interesting. Um, so if I'm listening to his show, and I'm picking up different patterns, I can I can reference that back to to Greg. So that's really interesting. But here's the thing. The reason why people love Obsidian is because of these interrelationships. The idea that you could open a file, and then, you know, I just open this file, and then I'm like, oh, interesting, I mentioned Greg Heisenberg. I can click that and it goes to that file. That's interesting, right? It shows, it works more to it, uh, it works more like the way your brain works. Your brain connects these patterns all the time. Here's a, yeah, yeah. So I see why it's interesting, but how does this get me better output? Exactly, yeah. So the next thing is Obsidian released this new tool called Obsidian CLI, and what that allows you to do is it allows you to use Claude Code, and it can go, and it can read all of the files in your Obsidian vault, which is a folder of text files. But with the Obsidian CLI, it can give Claude Code not only those files that it can read and access, but it can also give Claude Code information about the interrelationships of those files. So you can see, so Claude Code can see that, oh, this file is connected to this file and this file and this file. That gets very interesting in terms of what Cloud Code can understand about you and what Cloud Code can understand about all of the relationships between the things that you're working on. It can start to surface patterns about what you're thinking about that you are not seeing for yourself. Some idea that you might have been writing about for a year in this vault, it could be a latent idea, and it can just immediately say like, hey, did you know that you've been writing about this same pattern in startups or in this particular project you're working on, and every single note you're making across these different domains? And and in seeing that for the first time can be like a huge light bulb effect. It can cause like huge progressions in your learning and your understanding and your point of view on the world, but also in what you're working on. Um, so I've written out, I wanted to demonstrate how that actually works in terms of how I can pass information into an agent that would be impossible without Obsidian and Claude Code. So here's some commands that I have that I use, and I don't want you to be afraid of like all this stuff. I know this can look intense, but, um, here here's what, here's what I've got, some commands, and this is just terminal that I've created, and I'm running it in Obsidian. You don't need to use this, you can just also do this in your own terminal session on in whatever tool you want. But I put it in Obsidian because I want to see it all together, and I wanted to show you the ways in which you can like integrate and customize this environment.
[25:24]So here's a cool thing, so context slash context, load full context about my life, work, and current state. Reads context files, daily notes, and follows backlinks to build a complete picture. So I'll just show you that right here.
[25:55]So like, let's say I open a new session in in Cloud, just on my desktop, and now it's like I'm about to work on something. But before I work on it, I can just type context demo. Now, it's going to read a whole bunch of files about where I'm currently at, done. Like I've already pre-loaded, I've already pre-loaded in all this context now, so you can see it's going to start reading all these files. It's reading a read me, it's reading context about new, which is a media company that I'm working on. It's reading about other stuff, it's reading my personal workflow context, the other stuff is my show, it's reading the personal workflow context, and so I don't have to worry about it not knowing the key information that I wanted to know. I just did that one command, and now it's going to get all that information, done. So I can use slash today, which is a morning review, it pulls calendar, tasks, I messages, and the past week of daily notes into a prioritized plan for the day. Why does this matter? Well, okay, sure, you can set up an agent and give it access to your calendar and your tasks and I messages and things like that, but it's that that that doesn't have all of the information about what you're thinking about and why. If I'm writing daily notes about some particular technology or project or thing that I'm interested in, does my calendar reflect actively like, does it match the subjects I'm actually writing about? If an agent has that context, you can it can it can, uh, more effectively give you, um, information about what you should do or not do, or it can more effectively make decisions on what should be in your calendar or not in your calendar.
[27:48]Here's another one, slash close day.
[27:55]End of day processing, it extracts action items, surfaces vault connections, checks if confidence markers need updating. So I have a bunch of hypotheses that I I think about and I give them a confidence rating. This is an idea I'm working on, I feel very solid about it. Here's another idea I'm working on, I'm not sure about it. So these are like, um, daily operations things. But this is what I use Obsidian for the most, which is thinking tools.
[28:32]I really, really, really like working with LLMs as a thinking partner. That's my favorite way of using LLMs. I know people like to use agents and LLMs to build things, but I really like using them to think alongside me and build when I feel like, you know, I really have a novel way of viewing things.
[29:09]So let's see here, um, so Ghost, here's here's a command I have. It answers a question the way I would. It builds a voice profile from the vault, writes in that voice, then evaluates the fidelity. So I can just say, what do I think of AI? And I'm going to show you this. Challenge topic, it pressure tests current beliefs using the vault's own history, finds contradictions, counter-evidence, and shifts in thinking. Why does that matter? Well, if I want to make sure that I'm continually developing as a human being, and as a as a as in my skills, I want to make sure that, you know, the POV I have isn't overly biased or limited. So this can challenge me. Emerge, surfaces ideas the vault implies but never states, conclusions from scattered premises, unnamed patterns, unarticulated directions. This is super, super useful because a lot of times, you know, I I can be stuck just surfacing ideas in a in a in a lot of different ways, like for years. And just having someone say a simple thing to me that just says, hey, this is just naming the idea, hey, did you know that you keep circling around this pattern? Huge breakthroughs. Slash drift. It compares it compares my stated attention intentions against actual behavior over 30 to 60 days. Surfaces what I'm avoiding. Ideas. People on this podcast, the listeners will probably like this one. Deep 30-day vault scan with cross-domain pattern detection and graph analysis to generate ideas across all domains. This gives me, um, not just ideas on like things I should work on. Like it gives me ideas for tools and things like this, but it also gives me ideas on like films I should watch, products I should buy. Again, all influenced by like like things I'm writing about in my vault.
[31:09]Um, trace tracks how an idea has evolved over time across the vault. So let's see some of this stuff. The trace demo. So I did this one already, and the way this would work is I just like create a tab here, and I could just be like, Cloud Trace. And I had to create demo versions of all of these commands because of how much personal information is in my vault. But still, I don't even know like I I I can't even control what is going to show up on the screen, right? Um, but that's part of doing demos like this, which is which are kind of weird and interesting. But you can see personal agent infrastructure, it links to like Agenc AI, there's like a link here to Telegram. There's a link here to like Toby, the founder of Shopify. There's a link to like presence log, Cloudbot, you know, and then here's like, I I have a podcast too called the other stuff, and like you can see I'm obviously doing a lot of like thinking about that a lot, right? And so I can also, let's say if I go to Greg Heisenberg, and I go to local graph, so here's like all the times I've written about Greg Heisenberg, right? Notes on time constraints, how I use Obsidian, which is just kind of interesting. Um, so if I'm listening to his show, and I'm picking up different patterns, I can I can reference that back to to Greg. So that's really interesting. But here's the thing. The reason why people love Obsidian is because of these interrelationships. The idea that you could open a file, and then, you know, I just open this file, and then I'm like, oh, interesting, I mentioned Greg Heisenberg. I can click that and it goes to that file. That's interesting, right? It shows, it works more to it, uh, it works more like the way your brain works. Your brain connects these patterns all the time. Here's a, yeah, yeah. So I see why it's interesting, but how does this get me better output? Exactly, yeah. So the next thing is Obsidian released this new tool called Obsidian CLI, and what that allows you to do is it allows you to use Claude Code, and it can go, and it can read all of the files in your Obsidian vault, which is a folder of text files. But with the Obsidian CLI, it can give Claude Code not only those files that it can read and access, but it can also give Claude Code information about the interrelationships of those files. So you can see, so Claude Code can see that, oh, this file is connected to this file and this file and this file. That gets very interesting in terms of what Cloud Code can understand about you and what Cloud Code can understand about all of the relationships between the things that you're working on. It can start to surface patterns about what you're thinking about that you are not seeing for yourself. Some idea that you might have been writing about for a year in this vault, it could be a latent idea, and it can just immediately say like, hey, did you know that you've been writing about this same pattern in startups or in this particular project you're working on, and every single note you're making across these different domains? And and in seeing that for the first time can be like a huge light bulb effect. It can cause like huge progressions in your learning and your understanding and your point of view on the world, but also in what you're working on. Um, so I've written out, I wanted to demonstrate how that actually works in terms of how I can pass information into an agent that would be impossible without Obsidian and Claude Code. So here's some commands that I have that I use, and I don't want you to be afraid of like all this stuff. I know this can look intense, but, um, here here's what, here's what I've got, some commands, and this is just terminal that I've created, and I'm running it in Obsidian. You don't need to use this, you can just also do this in your own terminal session on in whatever tool you want. But I put it in Obsidian because I want to see it all together, and I wanted to show you the ways in which you can like integrate and customize this environment.
[35:24]So here's a cool thing, so context slash context, load full context about my life, work, and current state. Reads context files, daily notes, and follows backlinks to build a complete picture. So I'll just show you that right here.
[35:55]So like, let's say I open a new session in in Cloud, just on my desktop, and now it's like I'm about to work on something. But before I work on it, I can just type context demo. Now, it's going to read a whole bunch of files about where I'm currently at, done. Like I've already pre-loaded, I've already pre-loaded in all this context now, so you can see it's going to start reading all these files. It's reading a read me, it's reading context about new, which is a media company that I'm working on. It's reading about other stuff, it's reading my personal workflow context, the other stuff is my show, it's reading the personal workflow context, and so I don't have to worry about it not knowing the key information that I wanted to know. I just did that one command, and now it's going to get all that information, done. So I can use slash today, which is a morning review, it pulls calendar, tasks, I messages, and the past week of daily notes into a prioritized plan for the day. Why does this matter? Well, okay, sure, you can set up an agent and give it access to your calendar and your tasks and I messages and things like that, but it's that that that doesn't have all of the information about what you're thinking about and why. If I'm writing daily notes about some particular technology or project or thing that I'm interested in, does my calendar reflect actively like, does it match the subjects I'm actually writing about? If an agent has that context, you can it can it can, uh, more effectively give you, um, information about what you should do or not do, or it can more effectively make decisions on what should be in your calendar or not in your calendar.
[37:48]Here's another one, slash close day.
[37:55]End of day processing, it extracts action items, surfaces vault connections, checks if confidence markers need updating. So I have a bunch of hypotheses that I I think about and I give them a confidence rating. This is an idea I'm working on, I feel very solid about it. Here's another idea I'm working on, I'm not sure about it. So these are like, um, daily operations things. But this is what I use Obsidian for the most, which is thinking tools.
[38:32]I really, really, really like working with LLMs as a thinking partner. That's my favorite way of using LLMs. I know people like to use agents and LLMs to build things, but I really like using them to think alongside me and build when I feel like, you know, I really have a novel way of viewing things.
[39:09]So let's see here, um, so Ghost, here's here's a command I have. It answers a question the way I would. It builds a voice profile from the vault, writes in that voice, then evaluates the fidelity. So I can just say, what do I think of AI? And I'm going to show you this. Challenge topic, it pressure tests current beliefs using the vault's own history, finds contradictions, counter-evidence, and shifts in thinking. Why does that matter? Well, if I want to make sure that I'm continually developing as a human being, and as a as a as in my skills, I want to make sure that, you know, the POV I have isn't overly biased or limited. So this can challenge me. Emerge, surfaces ideas the vault implies but never states, conclusions from scattered premises, unnamed patterns, unarticulated directions. This is super, super useful because a lot of times, you know, I I can be stuck just surfacing ideas in a in a in a lot of different ways, like for years. And just having someone say a simple thing to me that just says, hey, this is just naming the idea, hey, did you know that you keep circling around this pattern? Huge breakthroughs. Slash drift. It compares it compares my stated attention intentions against actual behavior over 30 to 60 days. Surfaces what I'm avoiding. Ideas. People on this podcast, the listeners will probably like this one. Deep 30-day vault scan with cross-domain pattern detection and graph analysis to generate ideas across all domains. This gives me, um, not just ideas on like things I should work on. Like it gives me ideas for tools and things like this, but it also gives me ideas on like films I should watch, products I should buy. Again, all influenced by like like things I'm writing about in my vault.
[41:09]Um, trace tracks how an idea has evolved over time across the vault. So let's see some of this stuff. The trace demo. So I did this one already, and the way this would work is I just like create a tab here, and I could just be like, Cloud Trace. And I had to create demo versions of all of these commands because of how much personal information is in my vault. But still, I don't even know like I I I can't even control what is going to show up on the screen, right? Um, but that's part of doing demos like this, which is which are kind of weird and interesting. But you can see personal agent infrastructure, it links to like Agenc AI, there's like a link here to Telegram.
