How I Turned Claude Into My Personal Assistant (Complete System)
CChase AI
Computing/SoftwareAdvertising/MarketingSmall Business/StartupsInternet Technology
Transcript
00:00:00Claude should be running your life, or at least all the boring parts.
00:00:04And it's actually very easy to turn Claude into your own personal assistant,
00:00:07saving five to 10 hours every single week, just like I have.
00:00:10Now, we've talked about creating your own Claude OS on this channel before,
00:00:13whether that's a web-based setup like this one that includes voice
00:00:17or an Obsidian-based command center.
00:00:20But in all those videos, we tended to focus really on system design,
00:00:24how we should create our skill architecture,
00:00:26and how we should set up the actual Obsidian Vault.
00:00:29But today's video is going to be a little different.
00:00:31This one is going to look at my exact personal assistant setup,
00:00:35the skills and automations I use to run my business, my channel, my research, all of it.
00:00:41So you can get a good idea of what you need to do to recreate yourself.
00:00:45Now, when it comes to these custom fancy dashboards and command centers like you see here,
00:00:49we will get to that at the very end because there is some value in creating these
00:00:52when it comes to personal assistant setup.
00:00:54But the first thing we need to establish is,
00:00:56what the heck is this personal assistant even going to be doing?
00:00:59What is the boring, redundant work that we can automate and turn into skills?
00:01:04Well, for me, there's really three different buckets that I operate in that has a lot of like
00:01:08sort of drudgery, right?
00:01:10That takes up an inordinate amount of time, doesn't really require a lot of decision making,
00:01:14but it's just like grunt work that I offload to Claude Code.
00:01:18And those three buckets are productivity and sales.
00:01:21I kind of put that in the same category.
00:01:23Research and then content.
00:01:24So the productivity and sales stuff has a lot to do with my AI agency business.
00:01:28And then the research and content kind of fall in sort of the social media sphere.
00:01:32Makes sense.
00:01:33Now, the nice thing about this is a lot of what you're going to see here,
00:01:37I think does translate to almost everyone outside of the content stuff.
00:01:42I know a lot of people aren't creating content, but chances are you are working in some sort of
00:01:46sales or marketing environment where you have information coming in from clients or customers
00:01:51and you need to respond to them and you need to be able to do some sort of daily research
00:01:55to stay on top of whatever it is you're staying on top of.
00:01:57So a lot of what you see here, while it's specific to me, is something that can translate to you.
00:02:02Now, what we will look at here is probably what's going to give you the most immediate value.
00:02:05And this is sort of the productivity section.
00:02:06And it all spawns from this, the email triage automation.
00:02:11Now, the email triage skill does the following.
00:02:13Every morning at 8 a.m., it takes a look at my Gmail inbox.
00:02:16It uses the Claude connector to do so.
00:02:20It takes a look at everything that's come in over the last 24 hours and it puts it into a series
00:02:24of buckets, either leads, urgent, warm, sponsors, meetings, or noise.
00:02:30Once it has all the emails broken out into those specific buckets, it then does different
00:02:34things depending on the bucket, specifically the leads bucket and the sponsors bucket.
00:02:41Now, if it's a sponsor, Claude then automatically drafts up a reply with a boilerplate response
00:02:46and a link to my media kit saying, hey, here's what the prices are X, Y, and Z.
00:02:50However, if it's a potential lead, we then begin a process that is a little bit more in-depth.
00:02:54So on my website, every lead fills out a form saying essentially their budget, what they're
00:02:57looking for, their timeline, all the standard stuff.
00:03:00All this information is picked up by Claude Code in this inbox triage.
00:03:04From there, what it does, if it thinks it's a real query, so the email makes sense, they
00:03:09actually spent time on their response, the budget aligns, and it wasn't someone just putting in
00:03:13random nonsense, Claude then kicks off a web search.
00:03:17So just some background on who their company is, takes a look at their email, basically tries to
00:03:22get me just some preliminary information so I know what I'm doing if I walk into a potential
00:03:27discovery call with them.
00:03:28From there, Claude then gives me a recommendation saying, here's what I found out, here's what
00:03:32they want to do, should you move forward, should you not?
00:03:34I'm still the arbiter here of whether we go forward or not, obviously.
00:03:37If I say, yeah, let's do it, it then creates a draft email with a response as well as a link
00:03:43to my calendar so they can set up a meeting for me.
00:03:46If not, it just skips them.
00:03:47For all the emails in other buckets, if it's urgent, it's going to give me a potential drafted
00:03:51reply.
00:03:52But for everything else, it's just kind of marking them and what it also does is it gives
00:03:56me a full report, a written markdown file that goes into my obsidian vault that acts as a
00:04:00summary that I can read in a glance.
00:04:02The report looks something like this and then also lists all the noise that I don't really
00:04:05care about.
00:04:05And so with the simple setup, I save a ton of time every single day because I don't have
00:04:08to read all my emails.
00:04:09I don't have to manually filter every single lead.
00:04:12And if it thinks the lead makes sense, it's already done some preliminary research and drafted
00:04:16the response for me.
00:04:17And this is something you can very easily adapt for your own purposes.
00:04:20What sort of emails do you normally get?
00:04:22How can you put them in different buckets?
00:04:24And then more importantly, what do you want Cloud Code to do with the information it has
00:04:29once it's sorted everything?
00:04:30Now, the other half of the equation that saves me a ton of time is proposals and follow-ups.
00:04:33And this is what I do with clients after we've already had the discovery call.
00:04:37So I use Calendly.
00:04:38So post-discovery call, what I get in my inbox is a recap.
00:04:43Calendly automatically gives me a summary that includes all the key points of everything we've
00:04:47discussed.
00:04:48That recap then gets sent to Claude Code.
00:04:52Claude Code takes that recap and generates a branded PDF breaking down.
00:04:57Here's essentially what we're going to create.
00:05:00Here's the scope of work.
00:05:01Here's the pricing.
00:05:02Here's the form for you to sign.
00:05:04Let's go ahead and move forward.
00:05:05Now, obviously, I'm going to take a look at all that, but that saves a ton of time versus
00:05:09having to manually create some sort of proposal.
00:05:12From there, it generates a drive link that is sent to the client and the draft that includes
00:05:16the link itself.
00:05:17Now, this is what the proposal looks like.
00:05:19And this is just a dummy version.
00:05:20So I don't show any like client information on here, but breaks down the engagement, shows
00:05:24the timeline, and then shows the investment.
00:05:27And then at the very bottom, it just has some room for signatures.
00:05:30Now, lastly, in regards to follow-ups, that's a little more specific to some of like the AI
00:05:34audits I run.
00:05:35So I'm not going to go deep into that here since it's kind of technical and really won't
00:05:38apply to 99.9% of you.
00:05:40But that, in a nutshell, is kind of the productivity sales side of my Claude code personal assistant.
00:05:47Again, it doesn't have to touch every single thing you do.
00:05:49But like you saw here, a lot of this is just boring stuff that otherwise I would be spending
00:05:54hours a day on.
00:05:55So what are you spending hours a day on or hours a week on that we can offload to Claude?
00:06:00You should be doing it.
00:06:01Now, before we move into the research portion of my personal assistant, a quick word from
00:06:07today's sponsor, me.
00:06:09So I just released my Claude code masterclass, which is the number one way to go from zero
00:06:12to AI dev, especially if you don't come from a technical background.
00:06:15We focus on real use cases like the personal assistant stuff we're talking about today.
00:06:20And I go over other AI tools.
00:06:23I also have a codex masterclass in this community as well.
00:06:26So if you want to get serious about learning AI, this is the place to be.
00:06:30I'll put a link to it down below.
00:06:32And everything you see here, my exact setups, the Java system, the Obsidian Command Center,
00:06:36can also be found inside this community.
00:06:39So now let's talk about research.
00:06:40Now, obviously, mine is going to be all AI focused and yours may or may not be.
00:06:44So what you need to keep in mind is the idea that all of this spawns from knowing where your
00:06:50information originates.
00:06:52In the AI space, that's really a handful of places.
00:06:55It's like Twitter, GitHub, and then sometimes things will merge on YouTube first.
00:07:00But that's kind of it.
00:07:01Those are kind of the big three.
00:07:02So that's where we're going to go for information.
00:07:04Where you need to find your information for your niche, you got to figure it out.
00:07:08I can't tell you that.
00:07:09So you got to figure that out.
00:07:11But once you know that sort of source of knowledge, the setup is exactly the same for how I do
00:07:15it.
00:07:15So first things first, my main automation is my daily brief, right?
00:07:21My daily brief goes out to those wells, those sources of knowledge and figures out what the
00:07:27heck is going on.
00:07:27And so for me, like I said, that's really X, that's YouTube, and that's GitHub.
00:07:32Now, the GitHub setup is simple enough for me.
00:07:35Here's one from last week.
00:07:36And what it does is it uses the GitHub API to find the top trending AI GitHub.
00:07:41And it breaks it out in a few categories.
00:07:42I look at like the top 10 trending for the week.
00:07:44So what was created this week?
00:07:46I look at the top five trending from those that were created within the last 30 days.
00:07:50And then I look at the fastest growing over the last 24 hours and the last 30 days.
00:07:57So what's new and growing and then what's kind of been around and it's kind of like shooting
00:08:00up the charts.
00:08:01This gives you like a good idea of like, okay, what are people actually playing around with
00:08:04these days in the AI space?
00:08:05Because this changes literally daily and it's impossible to like know about it unless you
00:08:10actually looking at GitHub.
00:08:11And then we have Twitter, YouTube, and also a general web search.
00:08:14So I'm able to pull the big headlines.
00:08:16I can see what's trending on YouTube.
00:08:18Importantly, it shows me the creator and the views and their subs.
00:08:21So that kind of gives you a good idea.
00:08:22Like, I don't care if someone with a million subs gets 10,000 views.
00:08:24But if some dude with 2,000 subs has 10,000 views, then clearly he's talking about something
00:08:29that people care about.
00:08:30And then also we look at Twitter.
00:08:33And beyond that, it does some basic analysis on like, hey, here's some content opportunities.
00:08:38But to be totally honest, when it comes to figuring out, hey, here's what the research shows and
00:08:43here's what we should actually talk about, AI is pretty hit or miss with that.
00:08:46What we really care about here is sort of just the raw data it's able to bring.
00:08:49And again, what's the big sell here?
00:08:50The big sell is I don't have to do all that myself.
00:08:52Am I still manually going to go on Twitter and YouTube and go through my subscriptions for,
00:08:57you know, five, 10 minutes a day?
00:08:58Sure, of course.
00:08:59But this stops that from being like a 30-minute process.
00:09:03It saves me time to time, especially on the GitHub side.
00:09:05To do that manually would be terrible.
00:09:07End of note, this research daily brief and this email triage brief we spent a bunch of
00:09:12time on, these are actually combined into a single automation that I just call like my
00:09:16morning automation.
00:09:18And this is set up as a routine inside of Claude code.
00:09:22So it's a local routine, runs on my computer as long as it's open and just fires off those
00:09:27automations automatically.
00:09:28Now, as for the rest of the research side, I have what I call my xPulse or this gets kind
00:09:32of a pulse on Twitter, as well as my YouTube dives, which are on demand and deep research,
00:09:36which is on demand.
00:09:37Now, the Twitter setup is something that is actually an app that I built that lives on
00:09:43Railway.
00:09:44So this lives on Railway.
00:09:46It's working 24-7.
00:09:47And what it does is it sends me messages on Telegram every hour or so, showing me the top
00:09:54tweet in the AI space that's trending.
00:09:56And this is also tied to a lot of the major creators, especially ones who are on like the
00:10:00Claude dev team and the OpenAI team.
00:10:02So if something is popping off, something big has opened up in the AI space, I know about
00:10:07it immediately.
00:10:08I don't have to sit there on Twitter refreshing all the time.
00:10:11So the first half, the daily brief and the xPulse are, you know, those are automated.
00:10:17These two are automated.
00:10:18I don't even have to think about them.
00:10:19These two, YouTube dives and deep research, these are specific on-demand skills.
00:10:23I can use whenever I find some topic that I care about and I want to learn more about.
00:10:28Now, deep research is super basic.
00:10:30And by basic, I mean, it's already a command set up inside of everybody's WOD code.
00:10:35So if you do forward slash deep research, that is a essentially preloaded dynamic workflow.
00:10:40It will spawn, if you just let it go nuts, up to like 100 sub-agents that do like adversarial,
00:10:46essentially, information gathering.
00:10:48Like they'll go on the web, they'll find information, then they'll test it against each other to see
00:10:51if it's right and do some synthesis versus your standard web search where you just send Claude
00:10:55code.
00:10:55If you say, hey, Claude, go find me information about, you know, Fable 5, it's just going to
00:10:59send a couple of sub-agents to browse the web.
00:11:01This is that on steroids, but it eats up a ton of tokens, but it's something like a lot of
00:11:05people don't actually use.
00:11:06I also have what I call my YT pipeline skill.
00:11:11And so what that does is it then searches YouTube to find videos that are relevant to whatever
00:11:19I'm asking about.
00:11:19It then sends all those URLs to Notebook LM.
00:11:23Notebook LM itself then takes all the transcripts, does all the synthesis and sends that to me.
00:11:29Now I do that using a specific CLI, which is the Notebook LM Pi CLI, which actually gives
00:11:34Claude Code essentially an unofficial API to Notebook LM.
00:11:37Again, being able to do that means I get all the power of Notebook LM, but it doesn't cost
00:11:41me tokens to have Notebook LM and Google servers do all that synthesis on YouTube transcripts,
00:11:46which again, what are we doing here?
00:11:48We're trying to save time.
00:11:49I don't want to watch 10 YouTube videos about a specific topic.
00:11:52Just give me the summary.
00:11:53Do the synthesis.
00:11:54Tell me what's the throughput between all 10 videos.
00:11:57Tell me where they aren't aligned.
00:11:58And then tell me why I should care.
00:12:00And you put all that together and essentially what you get is a research setup that saves
00:12:06me undoubtedly five to 10 hours by itself minimum from this.
00:12:11If I try to do all this research on my own, I'd be dying.
00:12:13You know, I would be seriously struggling.
00:12:15And I think for a lot of people, again, whether you're doing AI-based searches or not, I think
00:12:20the productivity side and this research side should really go hand in hand.
00:12:24There's a ton of places I imagine in your domain where the sort of emails you respond to, the
00:12:30sort of things you're creating are based on certain research.
00:12:33So why aren't we sort of combining these things?
00:12:35Again, especially if these are like lower level, you don't really have to make decisions
00:12:38type tasks and just hand it over to a personal system of cloud code and have it do that for
00:12:42you automatically.
00:12:44Now, the last bucket here is content.
00:12:45And I'll spend the least amount of time here because I think this is the least relevant
00:12:48for most people.
00:12:49But just for those of you who might be doing content and want to know how I do it, for me
00:12:54specifically, when it comes to scripting hooks and outlines, this is simply a single on-demand
00:13:00skill.
00:13:01Now, I really like Callaway, super good creator on YouTube.
00:13:05So I essentially trained Claude on a bunch of his videos to create those skills in terms
00:13:10of here's how you should do a hook, here's how you should think about transitions and that
00:13:13sort of thing.
00:13:13But to be honest, I'm not someone who really does scripts.
00:13:16So this is just more of a brainstorming tool for me, but it is useful.
00:13:20I don't rely on AI to come up with the words that I say, but oftentimes it's nice to have
00:13:25a back and forth where you have some semblance of an idea, you bring it to AI, it's been trained
00:13:30on certain skills, so it's not just giving you generic garbage.
00:13:33And through that back and forth, some ideas, you know, kind of coalesce for you, the actual
00:13:37human being.
00:13:38So in terms of hooks and outlines, that's how I approach it.
00:13:41I know some people have everything scripted, just not how I work.
00:13:44Then we have packaging, again, similar to my hooks and outlines.
00:13:47I don't have it just create the titles or create the thumbnails, the thumbnails, I pretty
00:13:50much do all on my own.
00:13:52And then in terms of the titles, yes, it uses the same sort of like Callaway things where
00:13:56it's like, hey, here's the sort of words that you use, the sort of like psychological triggers,
00:13:59however you want to say it.
00:14:00But at the end of the day, it's more of a back and forth.
00:14:02I have it look at what titles I've done well and why.
00:14:06And it just, again, if it's just you and a piece of paper and you're trying to come up
00:14:09with everything 100%, I think you're going to struggle.
00:14:12And I think you also struggle if you just try to offload all creative purpose to AI because
00:14:16it's just not that good at these things that require quote unquote taste.
00:14:20But I think some sort of mixed approach helps a lot.
00:14:23But lastly, where AI really comes in handy for me is content repurposing.
00:14:28Now, this goes beyond just like dropping a video in a folder and it puts it across a bunch
00:14:32of different platforms.
00:14:33What this does is every day, twice a day at noon and 8 p.m., it looks to see if a new
00:14:38YouTube video has been posted by me.
00:14:40From there, it runs this content cascade skill where it then fetches the transcript from that
00:14:45video.
00:14:46And then it rewrites a blog, a LinkedIn post, and a tweet based on that transcript.
00:14:55Now, that skill took some time to get together because it's all about getting your voice correct.
00:15:00And your voice is your voice.
00:15:02It's unique.
00:15:03No one can tell you how to create a skill that's going to like work best for that.
00:15:06My suggestion, if you want to do something like this and have it do these sort of things,
00:15:10is you need to have examples of your own writing that you've done 100%.
00:15:13And what you do is you have a consistent back and forth.
00:15:15And it's kind of like a cycle, right?
00:15:17So I give Claude examples of my writing.
00:15:21I then say, turn that into a skill.
00:15:24Okay.
00:15:24It's then going to run that skill and it's going to give you its example.
00:15:29And what are you going to do?
00:15:30You're going to destroy their example.
00:15:32You're going to absolutely eviscerate it and say, this is wrong.
00:15:34This is wrong.
00:15:35This is wrong.
00:15:35This is right.
00:15:36Here's how we'll change this.
00:15:38So then you give them the updated example.
00:15:40It updates the skill.
00:15:41It gives you a new example.
00:15:43You destroy it.
00:15:44You do this over and over again for like 10 times.
00:15:47And then you continue to do it over and over again when you do it live.
00:15:50And over time, you will eventually get a skill that works for you.
00:15:55That's really the only way to do it.
00:15:56There's a huge human in the loop component if you're doing any sort of like humanizing or
00:16:01in your voice type writing.
00:16:03So don't listen to anybody that says, hey, here's just like this.
00:16:05Here's this one shot skill that's self-improving.
00:16:07No, no, no.
00:16:08You have to be in the loop.
00:16:09And that's the way to do it.
00:16:10And so in this case, I did it for a blog because it's a little different voice for a blog versus
00:16:15a LinkedIn post versus a tweet.
00:16:17And to be honest, I'm very lazy in terms of actually posting these tweets.
00:16:20But LinkedIn and the blog post, totally viable.
00:16:24And again, it comes from a single YouTube video.
00:16:26I don't have to think about it.
00:16:27It's automatically posting these things, putting it in my voice because otherwise I just wouldn't
00:16:31do it.
00:16:32So that is the meat and potatoes of my personal assistant setup with Claude, the automations
00:16:36and skills that I actually use.
00:16:38Now, what I hope you got from that is that this is unique.
00:16:42These are the things that I've identified that I don't really want to spend time on so I
00:16:46can spend my time doing things that I consider higher leverage.
00:16:49I don't want to do emails.
00:16:50I don't want to do a ton of research in the morning if I don't have to.
00:16:53And I don't want to repurpose my content.
00:16:55I don't want to have to manually write every proposal or filter every lead.
00:16:59Only you can identify what those sort of issues are for you.
00:17:02But the point is, once you identify them, you simply turn them into a skill.
00:17:05You make sure they work.
00:17:06You automate them.
00:17:08And you do that a few times.
00:17:09And all of a sudden, like you are saving five to 10 hours a week with that simple setup.
00:17:15Now, to turn that into a more advanced, coherent system, however, requires some sort of structure.
00:17:20Cool.
00:17:20We're creating all these briefs.
00:17:21It's doing stuff with emails.
00:17:22It's creating content.
00:17:23Well, like, how do I give it like a brain?
00:17:26How do I make sure it's able to reference things it's done in the past?
00:17:29How can I take all these briefs?
00:17:30How can I put them on a single dashboard?
00:17:32That's where we start to get into like the Cloud OS videos and the Cloud OS type lessons.
00:17:37And in this last part of the video, we'll touch on that briefly because that is something
00:17:41we have done plenty of content on in the past.
00:17:43And I'll link that here as well.
00:17:45Now, this is where you hear everyone talking about Obsidian and a second brain with Cloud Code.
00:17:50Why do we care about Obsidian?
00:17:51Is Obsidian in itself necessarily changing the way Cloud Code works?
00:17:55The answer is not really, right?
00:17:58Even something like this is just sort of just a fancy visual knowledge graph.
00:18:02But what Obsidian can do is allow us to organize everything that's created in our personal assistant
00:18:09setup, which over time creates a map that we hand to Cloud Code so we can quickly and correctly, truthfully answer our questions.
00:18:19So how do we set up Obsidian in a way to do that?
00:18:21Well, luckily, it's pretty simple.
00:18:23The Carpathi method is the most common one you will see.
00:18:26I want you to imagine all of these things simply as folders.
00:18:30Okay.
00:18:30These are all just folders.
00:18:31At the top, we have the vault.
00:18:33This is the folder we have designated as the Obsidian vault.
00:18:36Underneath the vault as subfolders, we have multiple sections.
00:18:40We have the raw section.
00:18:41We have the wiki section.
00:18:42And we have the output section.
00:18:44We just need places to put information that makes sense.
00:18:47So raw is unstructured data.
00:18:49Like, hey, we had Cloud Code do a bunch of research on stuff.
00:18:52It hasn't done any synthesis.
00:18:53It's just dumping all that raw information here.
00:18:56Well, after it's, you know, gotten all this information, we probably want to turn it into some sort of report.
00:19:01Well, that goes into the wiki section.
00:19:04And, hey, we have that report.
00:19:05We want to turn this into a slide deck.
00:19:06Well, that goes into the output section.
00:19:09Simple enough.
00:19:09Now, underneath all those folders, you're going to have more subfolders.
00:19:13Because, hey, if I have a wiki folder, but I have a million different reports,
00:19:17how does Cloud Code know where it needs to go to find information?
00:19:21Well, underneath every folder, we're going to have an index document,
00:19:24what's essentially is like, you know, the table of contents for that subfolder that says,
00:19:28hey, here's where this is, here's where that is, et cetera, et cetera.
00:19:32So imagine we had, you know, essential reports about AI agents and RAG systems and content creation.
00:19:38And under those reports were even more detailed reports about specific things,
00:19:42like autonomous coding and tool use patterns.
00:19:44So in those subfolders, what would you have?
00:19:45You would have index.
00:19:46So you kind of get where I'm going with this.
00:19:49We have things broken out into different subfolders that make sense,
00:19:53depending on their use case.
00:19:54And in each subfolder, we have an index file that says,
00:19:59hey, here's everything in the subfolder.
00:20:00So that Cloud Code always knows where it's going.
00:20:03It can never get lost.
00:20:04Now, when I say get lost, is Cloud Code actually getting lost?
00:20:07No, but if it's not organized, what happens is we're going to increase the token cost, right?
00:20:14If we just rely on grep for everything, that isn't necessarily the most efficient way to do it.
00:20:18So if we don't have an efficient setup, it's going to increase the token cost.
00:20:22It's actually going to decrease the accuracy over time.
00:20:26As you get bigger and bigger file structures, and you have more and more things in there,
00:20:32you need some form of organization.
00:20:34This is essentially a filing cabinet for Cloud Code.
00:20:37And yeah, we get these cool knowledge graphs,
00:20:39but that sort of idea of the filing cabinet of the map is the real value play.
00:20:42And the second half of the equation is these sort of like command centers and dashboards.
00:20:45Like, cool, Cloud Code is my personal assistant.
00:20:47It's grabbing emails.
00:20:49It's doing research on contents, repurposing stuff.
00:20:51But like, where does that information go?
00:20:53Where does it live?
00:20:54Where can I see it?
00:20:55More importantly, can I see everything in one place?
00:20:58Yes, we can totally set that up.
00:21:00Now, can that place be the terminal?
00:21:03Not really.
00:21:05That's like not the purpose of the terminal.
00:21:07And it's not even really the purpose of the Cloud Code desktop app.
00:21:09So when we talk about these command centers,
00:21:12or we talk about some web app dashboard like this, that's the value, right?
00:21:15It's the one-stop shop that you really can't get anywhere else
00:21:18because it needs to be 100% customized.
00:21:20And you can really see that shine in the subsidiary base setup, right?
00:21:23I have all my metrics here, my token burn.
00:21:25I have all these different automations that we're talking about are here.
00:21:28I can essentially run them at a click of a button.
00:21:30The audience section here is essentially a different breakdown of that morning report.
00:21:35And the same sort of stuff lives here in the web app version as well.
00:21:38I got the metrics.
00:21:39I got the skills.
00:21:40Down here, I have the documents so I can pull up those reports.
00:21:43And this is the exact same thing I would find inside of my Obsidian Vault.
00:21:46Like it's all connected.
00:21:48So these dashboards give you the observability.
00:21:50Obsidian is what allows you to keep it all organized.
00:21:52And it's these sort of skills and automations that are actually saving you time
00:21:56and doing the work as a personal assistant, as an executive assistant.
00:22:00And so you put that all together and you have a way to make Cloud actually work for you.
00:22:04Essentially, totally hands-off.
00:22:06So that's where I'm going to leave you guys for today.
00:22:08I hope that was somewhat eye-opening in terms of how you should approach Cloud as a personal assistant.
00:22:13If you want to get your hands on the Cloud Code Masterclass or the skills I talked about today
00:22:16or any of these sort of dashboards, my exact setups can be found inside of Chase AI+.
00:22:20There is a link to that in the pinned comment.
00:22:22And as always, I'll see you around.