WEBVTT

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You use AI every day. Beat. But that doesn't

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actually mean you're an advanced user. Right.

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I mean, it definitely feels advanced, but daily

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casual use is really just the beginning. I think

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about this a lot. We type a quick prompt into

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a chat box. We get a really solid answer. We

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feel incredibly productive. Oh, yeah. Totally.

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Beat. But we are barely scratching the surface

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of what is possible. Welcome to this deep dive.

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Today, we're charting a very specific path. We

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are exploring the five levels of cloud proficiency.

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We're going to move step by step through this

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entire framework. We'll start with those simple

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everyday chats that will climb all the way up.

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We'll explore fully autonomous background workflows.

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Our goal is to help you pinpoint exactly where

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you are right now. Right. And more importantly,

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we want to show you how to level up safely. So

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let's start at the absolute baseline. Level one.

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the enthusiast. Yeah, which is honestly where

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most people tend to live right now. You might

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assume you're a total power user just because

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you chat with the AI every single morning. But

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realistically, this is just the ground floor.

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Level one is really built for quick daily tasks.

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You know, you need a fast email draft. You need

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a short summary of a long article. Right. Or

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maybe you just need a simple explanation of a

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complex topic. It just gives you a much faster

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starting point. You paste in some rough meeting

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notes. You ask the AI for a clean version. Yeah.

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A few minutes later, you have something totally

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useful. It helps you think faster. You create

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a solid first draft. And then you just finish

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the actual work yourself. There is a very specific

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tactic here that I love. One that works incredibly

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well when you're at level one. What's that? Uploading

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screenshots directly into the chat. Oh, yeah.

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That is a fantastic habit to build. You really

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need to stop typing out every single detail.

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It just takes way too much time. Exactly. Because

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you might accidentally miss something important.

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Just share exactly what you see on your screen.

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Exactly. So imagine you get a really confusing

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dashboard error, or you see a weird error message

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during your work. Right. You panic a little.

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Yeah. But you don't try to transcribe the code.

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You just snap a quick screenshot. You upload

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the image directly. Then you ask it to explain

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the error in simple English, and you ask for

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the very next step to fix it. It also works incredibly

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well for visual content, too. Say you're designing

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a new newsletter layout, you take a quick screenshot

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of the draft, you ask the AI to check the title

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length, or you ask if the call -to -action placement

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needs clearer wording. It's working straight

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from the real visual data. But there's a really

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massive limitation at this stage. a severe lack

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of ongoing context. Oh, completely. One -off

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chats are perfectly fine for single isolated

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tasks, but repeated ongoing work is entirely

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different. Exactly. Repeated work requires a

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very specific, consistent tone. It requires deeply

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knowing the target audience. You have internal

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company rules. Yeah. You have past business decisions

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to consider. And in a quick chat, the AI... basically

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forgets all of that. It has total amnesia. You

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have to repeat your tone and rules every single

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time. Honestly, I have a vulnerable admission

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to make here. Okay, let's hear it. Beep beep.

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I still wrestle with starting every repeated

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task in a blank chat. Oh, we all do it sometimes.

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It just feels faster in the heat of the moment.

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You just want an answer right now. Yeah, I do.

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But over a month you waste countless hours re

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-explaining yourself. It really makes me wonder

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about the true value here. Is level one basically

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just using Claude as a glorified short -term

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search engine? Pretty much. It's a fast starter,

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but it forgets everything by the next day. Which

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perfectly highlights the core problem we need

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to solve. We have to fix that blank chat amnesia.

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Yes. So let's step up to level two, the beginner.

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We fix this by building a persistent workspace.

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Level two is entirely focused on creating continuity.

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Your important work continues across multiple

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conversations. It continues across your files

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and your connected data sources. This level relies

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heavily on three core features, projects, memory,

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and past chat search. Right. Memory naturally

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retains your specific working preferences over

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time. Past chat search lets you easily find older

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conversations. If you can just open a chat and

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say, find the campaign direction from last week.

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Exactly. Then you ask it to prepare the final

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outline based on that. It seamlessly maintains

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the historical thread. But it gets really interesting

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when we bring in connectors. You can actually

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connect the AI to the information you already

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use. Yeah, this is a huge step up. Google Drive,

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Gmail, Slack, Google Calendar, Microsoft 365.

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Wow, that's a lot. Your real... actionable context

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already sits inside those apps. Connectors pull

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that securely approved information right into

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your active conversation. So you don't have to

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manually collect every single detail anymore.

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You don't have to constantly switch tabs to copy

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and paste. You can just ask it to review a specific

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client email thread. Right. Or review the latest

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strategic brief directly from Google Drive. Let's

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look at a very specific, practical example here.

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Creating a highly structured meeting summary.

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You upload your messy, raw client notes. Yeah,

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we've all been there. And you want a professional

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Word document out of it. The prompt for this

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needs to be very deliberate. You ask it to clearly

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include the meeting background. You explicitly

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ask for the confirmed decisions. You ask for

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a list of questions that still need confirmation.

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And finally, you demand a next actions table.

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That table must include the responsible person.

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and the specific deadline. But here is absolutely

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the most important part of that workflow. You

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give the AI a very strict, unbreakable rule.

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Which is? If any information is missing, Claude

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must write, not confirmed. It is absolutely not

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allowed to guess or fill in the blanks. I like

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to think about it this way. Level one is a public

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whiteboard that gets wiped clean every night.

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I like that. Level two is a dedicated office

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desk where your files stay exactly where you

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left them. That's a perfect way to picture the

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difference. It reliably turns messy inputs into

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clearly structured files of files you can actually

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review, trust, and use in your job. But I do

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have a lingering concern here. With all those

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connected apps, can we trust it not to just invent

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information? It's safer, but you still must review

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the structured output before sending it anywhere.

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Okay, so we've got our files beautifully structured

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on our metaphorical desk, but I'm still the one

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opening the folders and doing the actual manual

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labor. Right. I'm still clicking and dragging.

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Exactly. And that bottleneck is why you have

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to level up again. Welcome to level three, the

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intermediate. We've mastered text outputs. Now

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we give the AI actual hands. We're talking about

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a feature called Claude Cowork. This is where

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it actively starts operating your computer for

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you. It handles complex multi -step tasks directly.

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It moves way beyond just reading your text files.

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It actually starts manipulating the files on

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your machine. Okay. So imagine you have a wildly

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messy downloads folder. It's just stuffed with

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random invoices, notes, and PDFs. You can give

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Cowork a very specific multi -step directive.

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You literally tell it to sort that folder by

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file type. You tell it to rename every single

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file to a standard format, like year, month,

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day. Then you ask it to summarize the contents

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of all those files. And if a file is unreadable

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or unclear, it doesn't just crash, it neatly

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moves it to a dedicated folder. Like a needs

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review folder. Exactly. It does all the tedious

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heavy lifting for you. But we really need to

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talk about safe file access here. This is absolutely

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crucial. When you give an AI direct file access,

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you must start small. You have to set up isolated,

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protected folders. Specifically, you should have

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three distinct folders for this. Right. Source

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files, working files, and outputs. Let's break

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that down. Source files are the read -only documents

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it can look at. Working files are the temporary

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sandbox where it actively processes data. Outputs

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are the final finished results for you to manually

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check. Exactly. You never let it loose on your

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main hard drive. That's just asking for a disaster.

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This isolated structure leads to something really

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powerful, though. Reusable skills. Oh, yeah.

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When a tedious task repeats every single week,

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you save it as a skill. Let's use a weekly client

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report generator as a solid example. You build

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a custom skill to process marketing data every

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Friday. OK. You establish strict rules for the

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output. You require five specific sections every

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single time it runs. So you'd tell it, I need

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an executive summary at the very top. It's a

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short, crisp summary of the week's performance.

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Right. And then you force it to extract the key

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results. It pulls the important, verified metrics

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directly from the uploaded data. Right. And you

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want to compare those numbers to the previous

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week. So you add a section for important changes.

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Yeah, exactly. You're building a reliable, repeatable

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template. And you'd probably want it to flag

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anything that's missing, too. Definitely. That's

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your open questions section. It lists any unclear

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data points. Then it always ends with a clear

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next actions table. Action, owner, and deadline.

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Once you save that specific skill, your weekly

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workflow changes entirely. How so? You just upload

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the fresh raw data each week. You hit run on

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the skill. It automatically follows the exact

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same five -step process without you managing

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it. You can even schedule these simple tasks

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to run automatically. Say you're using a cloud

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desktop application. Yeah. You could easily set

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up a customized briefing for 7 .30 p .m. every

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weekday. It quietly checks your connected sources

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in the background. It stands Gmail. It checks

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your calendar. It reads your Slack messages.

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It pulls all that context together. Then it prepares

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a short summary of tomorrow's meetings and any

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pending actions. It feels incredibly powerful.

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But I really have to ask this. Isn't giving AI

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direct file access a recipe for accidentally

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deleting your hard drive? Only if you're reckless.

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Always use copy files in isolated folders to

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test first, sponsor. We're back! So we just covered

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automating desktop chores in Level 3. Now we

00:10:03.960 --> 00:10:06.460
really scale things up. We do. Welcome to Level

00:10:06.460 --> 00:10:09.240
4, the Advanced Builder. This is a major jump.

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This is where we introduce Claude code. We're

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moving away from simple folder sorting tasks.

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We're getting into complex multi -file project

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engineering. This requires a real dedicated project

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structure. And crucially, it requires a Claude

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.md file. Let's quickly define that jargon, a

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simple text file that tells the AI your project

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rules. It basically acts like a strict working

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guide for the system. It clearly defines the

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overarching project goal. It explicitly explains

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what all the main folders are actually used for.

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Right. It lists the specific files the AI is

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allowed to edit. And crucially, it lists the

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files it must absolutely leave unchanged. It

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also tells the AI exactly how to run your internal

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tests. And it defines what the final report format

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should look like. But there is a very critical

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step here that you cannot skip. You must ask

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the AI to plan and explain its approach first.

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Yes. It has to do this before it makes any actual

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edits. It's like asking a contractor for blueprints

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before they knock down a wall. You prompt it

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to read the folder structure. You ask for a detailed

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step -by -step plan. It needs to explain which

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files will change and exactly why. You review

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that plan. You approve it. Only then does the

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actual coding work begin. As these projects get

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bigger, things naturally get much more complicated.

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One single session can quickly become overloaded

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and confused. Yeah, for sure. So we have to deliberately

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split the workout. We split big work into parallel

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sessions. We use specialized tools like sub -agents

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and work trees. One stream handles the front

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-end layout. Another stream prepares the backend

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tests. A third stream carefully reviews the overall

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logic. This keeps the different work streams

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entirely separate and clean. They happen at the

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exact same time. but they don't accidentally

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interfere with each other's code. And you always

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have a mandatory non -negotiable review step

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built in. The AI absolutely must check the result

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before you accept the files. It must run all

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the available system checks. If a check fails,

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it has to explicitly explain the issue. It fixes

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the error itself. It runs the check again. Finally,

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it prints out a list of every single changed

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file. You carefully look at that list. You verify

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the changes. Then you formally consider the task

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complete. But I'm genuinely curious about the

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mechanics of this process. Why bother splitting

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tasks into parallel sessions instead of just

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one giant prompt? To keep the AI focused, preventing

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it from getting confused, and mixing up changes.

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That makes perfect sense. Clear rules. Clear

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inputs. Clear safety checks. Which finally brings

00:12:36.980 --> 00:12:39.179
us to the absolute summit of this framework.

00:12:39.700 --> 00:12:43.169
Level five, the architect. This is fully autonomous

00:12:43.169 --> 00:12:45.909
infrastructure. We're completely removing the

00:12:45.909 --> 00:12:48.809
human from the active day -to -day loop. We're

00:12:48.809 --> 00:12:51.610
finally entering the realm of true background

00:12:51.610 --> 00:12:53.669
automation. You've already set the strict rules

00:12:53.669 --> 00:12:57.049
in Level 4. Now, the complex workflow runs without

00:12:57.049 --> 00:12:59.950
you even sitting at the screen. But the hardest

00:12:59.950 --> 00:13:02.730
part of Level 5 isn't actually technical. Beat.

00:13:02.879 --> 00:13:05.820
It's trust. Trust is incredibly difficult here.

00:13:06.360 --> 00:13:09.419
You're letting an AI touch real files and critical

00:13:09.419 --> 00:13:12.019
business data in the background. Giving up that

00:13:12.019 --> 00:13:14.559
control is scary. You have to build this autonomy

00:13:14.559 --> 00:13:18.139
very, very slowly. At this advanced stage, tasks

00:13:18.139 --> 00:13:21.220
start from automatic triggers. a time schedule,

00:13:21.460 --> 00:13:24.179
a brand new email arriving, a specific GitHub

00:13:24.179 --> 00:13:27.340
event, or an external API call. We use a system

00:13:27.340 --> 00:13:29.639
called Cloud Routines for this. These are secure

00:13:29.639 --> 00:13:32.120
cloud -based workflows. They run entirely on

00:13:32.120 --> 00:13:34.299
Anthropic's own back -end infrastructure. They

00:13:34.299 --> 00:13:36.259
don't rely on your local desktop being turned

00:13:36.259 --> 00:13:38.200
on. So you can set a routine to automatically

00:13:38.200 --> 00:13:40.620
review changed files when a pull request opens.

00:13:41.120 --> 00:13:43.360
Or you could have it create a massive weekly

00:13:43.360 --> 00:13:45.899
project summary every Friday afternoon. But we

00:13:45.899 --> 00:13:48.220
desperately need safety mechanisms here. This

00:13:48.220 --> 00:13:50.460
is exactly where hooks come in. Let's define

00:13:50.460 --> 00:13:53.299
that term clearly. Safety gates that check the

00:13:53.299 --> 00:13:56.220
AI's actions before and after. Right. There's

00:13:56.220 --> 00:13:58.940
a pre -tool use hook. It acts just like a strict

00:13:58.940 --> 00:14:01.929
security gate. Before the AI actually runs a

00:14:01.929 --> 00:14:04.610
command, the hook checks it. If the proposed

00:14:04.610 --> 00:14:07.529
action is risky, like deleting important files,

00:14:07.889 --> 00:14:11.250
it blocks it instantly. It asks the AI to rethink

00:14:11.250 --> 00:14:13.470
and correct the action. Then there's the post

00:14:13.470 --> 00:14:16.049
tool use hook. After the tool successfully finishes,

00:14:16.509 --> 00:14:19.389
this hook handles the necessary cleanup. It might

00:14:19.389 --> 00:14:22.350
automatically format a text file. Or it might

00:14:22.350 --> 00:14:24.350
send you a quick Slack notification that the

00:14:24.350 --> 00:14:26.590
background task is done. The entire workflow

00:14:26.590 --> 00:14:29.399
is fully automated. But those precise hooks keep

00:14:29.399 --> 00:14:32.259
it tightly and safely controlled. You still want

00:14:32.259 --> 00:14:34.100
to start this process very safely though. We

00:14:34.100 --> 00:14:36.240
highly recommend starting with a daily private

00:14:36.240 --> 00:14:38.960
morning briefing. Yes. Just let it run quietly

00:14:38.960 --> 00:14:41.159
every morning at 6 a .m. It checks your upcoming

00:14:41.159 --> 00:14:43.600
calendar. It safely scans your important emails.

00:14:43.899 --> 00:14:46.120
Right. It reviews your missed slack threads.

00:14:46.480 --> 00:14:49.440
It prepares a comprehensive summary. But it sends

00:14:49.440 --> 00:14:52.190
that summary only to you. It doesn't email your

00:14:52.190 --> 00:14:54.990
boss. You review it over coffee before taking

00:14:54.990 --> 00:14:57.250
any action. Yeah, you let it run like this for

00:14:57.250 --> 00:15:00.269
a full week. You check if it misses nuances or

00:15:00.269 --> 00:15:02.730
messes up your actual priorities. You carefully

00:15:02.730 --> 00:15:05.110
adjust the background instructions. Only after

00:15:05.110 --> 00:15:07.870
definitively proved reliable do you give it a

00:15:07.870 --> 00:15:11.570
more important workflow. Exactly. Beat. Whoa.

00:15:11.909 --> 00:15:15.070
I mean, imagine truly scaling this up. Imagine

00:15:15.070 --> 00:15:17.990
an AI autonomously running your complex workflows

00:15:17.990 --> 00:15:20.700
in the background while you sleep. It's wild.

00:15:21.120 --> 00:15:23.679
Perfect checks. Perfect balance. Waking up to

00:15:23.679 --> 00:15:26.159
finished work. It's an absolutely amazing thought,

00:15:26.620 --> 00:15:29.620
but it clearly demands immense caution in planning.

00:15:29.740 --> 00:15:31.799
Which naturally raises a really big question

00:15:31.799 --> 00:15:34.539
for me. How do we stop an autonomous system from

00:15:34.539 --> 00:15:36.940
going rogue and sending a bad email? You use

00:15:36.940 --> 00:15:39.720
those hooks to block risky actions and strictly

00:15:39.720 --> 00:15:42.080
require human review first. Okay, let's bring

00:15:42.080 --> 00:15:43.799
this all back down to earth for a minute. We

00:15:43.799 --> 00:15:46.620
need a big idea recap to tie this together. The

00:15:46.620 --> 00:15:48.799
core insight from all of this source material

00:15:48.799 --> 00:15:52.340
is surprisingly clear. Advanced use isn't really

00:15:52.340 --> 00:15:55.279
about writing better, more clever prompts. It's

00:15:55.279 --> 00:15:58.080
entirely about clearer workflow design. You don't

00:15:58.080 --> 00:16:00.120
just magically jump to level five. You don't

00:16:00.120 --> 00:16:02.620
blindly rush into full automation. You have to

00:16:02.620 --> 00:16:04.460
build the foundational structure first. Yeah,

00:16:04.460 --> 00:16:06.820
you add proper folder structure, you add firm

00:16:06.820 --> 00:16:09.340
safety limits, you add mandatory review steps.

00:16:09.620 --> 00:16:12.419
That's how this technology becomes truly, reliably

00:16:12.419 --> 00:16:15.240
useful. So here is your practical takeaway for

00:16:15.240 --> 00:16:18.279
today. Look closely at your own workflow. Pick

00:16:18.279 --> 00:16:21.240
just one repeated week task that annoys you.

00:16:21.259 --> 00:16:25.159
Just one task and upgrade it by exactly one single

00:16:25.159 --> 00:16:27.340
level. If you're stuck at level one, make a project.

00:16:27.580 --> 00:16:29.759
If you already have a project, connect one live

00:16:29.759 --> 00:16:32.419
data source. If you have connected sources, try

00:16:32.419 --> 00:16:35.240
a basic co -work task. Build a safer, more structured

00:16:35.240 --> 00:16:38.899
workflow. Add a mandatory review step. One single

00:16:38.899 --> 00:16:41.559
intentional upgrade will teach you way more than

00:16:41.559 --> 00:16:44.299
trying to build a massive autonomous system on

00:16:44.299 --> 00:16:46.659
day one. It forces you to truly understand the

00:16:46.659 --> 00:16:48.379
underlying mechanics. It forces you to actually

00:16:48.379 --> 00:16:51.200
build trust with the tool. Step by step, level

00:16:51.200 --> 00:16:53.019
by level. That's how you actually get advanced.

00:16:53.500 --> 00:16:55.360
It's been a truly fascinating journey through

00:16:55.360 --> 00:16:58.159
these five levels today, from the eager enthusiast

00:16:58.159 --> 00:17:00.259
all the way up to the architect. But I want to

00:17:00.259 --> 00:17:03.019
leave you with a final slightly provocative thought

00:17:03.019 --> 00:17:06.059
to mull over. Beat. Let's say you successfully

00:17:06.059 --> 00:17:08.970
level up. You reach a point where AI flawlessly

00:17:08.970 --> 00:17:11.589
remembers your context, where it perfectly plans

00:17:11.589 --> 00:17:14.069
your complex projects, where it autonomously

00:17:14.069 --> 00:17:16.210
executes your daily routines with perfect hooks

00:17:16.210 --> 00:17:17.109
and safety checks.
