WEBVTT

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You spend 20 minutes perfectly explaining a task.

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You get the details just right. The formatting

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is flawless. Then you wake up the next morning,

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you open a new chat window, and it has completely

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forgotten who you are. Yeah, it's the classic

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amnesiac chat bot problem. I mean, we've all

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been there. It's incredibly frustrating, honestly.

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You're basically training a new employee from

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scratch every single day. Well, welcome to today's

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deep dive. We're shifting away from those temporary

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AI chats. The goal today is building a permanent

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living environment. We're calling it a co -work

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operating system, and we're doing it using Claude

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projects. So we have a really fascinating journey

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mapped out for you today. First, we'll clearly

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define the difference between standard Claude

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chat and this new co -work concept. Then we'll

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unpack the underlying architecture. It relies

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on three surprisingly simple text files that

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give the AI persistent memory. After that, we're

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mapping out structured workstations. And finally,

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we'll look at the advanced workflows to keep

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this whole system incredibly fast and cheap.

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Before we jump into the mechanics, I have to

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confess something. I still catch myself pasting

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the exact same five paragraph instruction prompt

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every morning. I'm just so conditioned to the

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old way of working. I still wrestle with prompt

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drift myself. Listen, it makes complete sense

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that you do. We've all been trained over the

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last few years to treat AI like a disposable

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tool. You use it, you close the tab, and it vanishes.

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But to build a true AI operating system, you

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have to completely change the environment. We

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need to start by looking at the three distinct

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flavors of Claude that currently exist. Right.

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Let's break down that baseline. We need to understand

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the environment before we can build the system.

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Exactly. So first, you have Cloud Chat. This

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is the web browser version. Everybody knows.

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It's great for doing some quick market research.

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It's helpful if you just need to draft a quick

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apology email to a client. But it starts fresh

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every single session. It has absolutely zero

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memory of what you did yesterday. It's essentially

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a blank slate every time you hit Enter. Then

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you have Cloud Code. Now, this is a very different

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beast. It's a terminal -based tool built specifically

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for developers. Meaning a text -only screen where

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programmers type direct system commands. Precisely.

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It connects directly to a software code base.

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It can actually autonomously edit files, run

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tests, and execute commands. But it's highly

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specialized for software engineering. It's definitely

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not built for your general day -to -day workflow.

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So if chat is entirely temporary and code is

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strictly for programmers, there has to be a middle

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ground, something built for persistent, everyday

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knowledge work. And that brings us to the third

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flavor, Claude Cowork. This is the actual desktop

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application. It's engineered specifically for

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long -term compounding workflows. The true magic

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here isn't just the AI itself. It's the ability

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to natively mount local folders from your computer.

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It maintains a persistent, evolving memory. And

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it uses external connectors to link directly

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to your gisting tools, things like Gmail, your

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Google Calendar, or your Notion databases. OK,

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let me try to contextualize this. Standard Cloud

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Chat is basically a temp worker. They show up,

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do a decent job. but they get a complete memory

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wipe every single night. It's literally like

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that movie, 50 First Dates. Beat. But co -work

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is fundamentally different. It's like hiring

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a full -time partner. You're giving them a dedicated

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desk. You're giving them a permanent filing cabinet.

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That desk analogy is perfect. You're giving the

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AI a physical home on your machine. It doesn't

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exist in a vacuum anymore. It has a spatial awareness

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of your digital life. But that raises a pretty

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massive privacy concern for me. Does mounting

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a local folder mean the AI is just freely reading

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everything on my computer? Is it scanning my

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personal photos while I sleep? No, absolutely

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not. The permissions are strictly ring -fenced.

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It only reads the specific folder you explicitly

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mount and allow inside the application. It has

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zero access to the rest of your hard drive. So

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it's a fenced -in playground, not a master key

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to my hard drive. Right. You dictate the boundaries.

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It only sees what you place inside the fence.

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Now that we understand Co -Work acts like a dedicated

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filing cabinet, we need to know what actually

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goes inside those folders. How does it physically

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remember us? This is where it gets genuinely

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fascinating. You would think an advanced AI operating

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system requires massive, complex databases. But

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the whole system runs on a surprisingly simple

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architecture. You literally just need three plain

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text files sitting inside a root folder. We'll

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call that master folder your Co -Work OS. Just

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three files. I mean, that feels almost too simple.

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Yeah, but they're just markdown files. Meaning

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basic text files with simple formatting headers

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and bullet points. Right. There's no complex

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programming logic. No Python scripts. The first

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file is called Claude .md. Think of this file

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as the master operating manual or the global

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routing map. When you open a new session, this

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file tells Claude what to load and where to look.

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It establishes the fundamental ground rules for

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how it should behave. Yes, and it has three core

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components. First is the memory system itself.

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It instructs Claude to always check your pass

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context before answering. Second is the routing

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map. This prevents the AI from guessing. If you

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ask a question about your taxes, the map routes

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it straight to your financial folder. Third,

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you have references. These are pointers that

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tell Claude where to find extra context, but

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only when it actually needs it. Two secs silence.

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I really have to push back here. It feels wild

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to me. The absolute cutting edge of artificial

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intelligence relies on basic text files from

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the 1990s to function. And the sources are very

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strict about this. They say we absolutely must

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cap this Claude .md file at 300 lines. Why cap

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it? If this is my master operating manual, why

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not dump every single rule, preference, and workflow

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I have in there? It's a really common trap people

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f— fall into to understand the cap, you have

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to understand how token limits actually work

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under the hood. Meaning the maximum amount of

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text the AI can process simultaneously. Think

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of it like the AI's cognitive battery power for

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a single conversation. Your large root files

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load every single time you start a new session.

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Every time you say hello, Claude has to silently

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read that entire Claude .md file first. If your

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manual is 20 pages long, it slowly drains your

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token limits before you even start working. It

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costs more money. It severely slows down the

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response time. Leaving barely any processing

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power to actually complete the task I asked for.

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Exactly. You're giving it cognitive overload.

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That's why you keep that main routing file under

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300 lines. It should be a traffic cop, not encyclopedia.

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Well, that makes a lot of sense. So if Claude

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.md is the traffic cop, what's the second file

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handling? The second file is memory .md. This

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functions as your running ledger. It holds your

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active, ongoing projects and your saved personal

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preferences. This specific file is the magic

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ingredient that stops your conversations from

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starting at zero every day. It's the actual continuity

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mechanism. Yeah, it tracks the reality of your

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current work. We usually split it into two sections.

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One section tracks active projects so it knows

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your upcoming newsletter is currently in the

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rough draft stage and you're struggling with

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the conclusion. The second section tracks granular

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preferences. Like knowing a specific client absolutely

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hastes bullet points and prefers numbered lists.

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Okay, and the third file in this architecture?

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That one is called VoicePrinciples .md. We usually

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drop this into a subfolder called Resources.

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This file's entire job is teaching the AI exactly

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how you write and communicate. We'll definitely

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dig into that voice file in a minute because

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sounding human is huge. But first, just managing

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these individual markdown files sounds potentially

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messy. If I'm manually editing text files all

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day, I feel like I'm stepping backward in productivity.

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That's a totally valid concern, and it's why

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a lot of power users rely on an app called Obsidian.

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It's a completely free markdown editor. You don't

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have to migrate anything. You just open your

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existing Cowork OS folder as a vault inside Obsidian.

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It instantly gives you a beautiful visual interface.

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You can easily view, link, and manage all these

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text files in one clean dashboard. But practically

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speaking, do I have to manually open that dashboard

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and type into memory .md every single time I

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finish a task? That feels like a lot of friction.

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No, not at all. That's the beauty of the system.

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You just tell Claude in your normal chat window

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to remember this. The AI takes your natural language

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instruction. reformats it, and silently writes

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it to the Markdown file automatically. You just

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talk to it and it updates its own memory notes.

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It completely removes the administrative burden.

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You just do your work and the system documents

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itself. Okay, so the AI can take its own notes.

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But let's circle back to that third file. How

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do we actually stop it from sounding like a generic,

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overly enthusiastic robot? And as we scale this

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up, how do we keep it from mixing up completely

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different parts of your life? Those are two separate

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but incredibly important challenges. That's where

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the voice system and the concept of workstations

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come into play. Let's tackle the voice system

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first. How do we actually build that voice principles

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file without it taking weeks of training? Well,

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you have to feed the AI real historical examples

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of your authentic writing. If your Gmail is already

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connected to your cowork app, you can literally

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just have it analyze your last 50 cent emails.

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If you don't want to connect your email, just

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copy and paste five to 10 past articles or reports

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you've written right into the chat. You ask it

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to reverse engineer your tone. Yes. But here's

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the critical failure point for most people. Vague

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rules fail miserably. If you tell Claude to be

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warm and professional, you're going to get terrible

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generic AI output. It'll sound like every corporate

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memo ever written. You have to extract highly

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specific mechanical rules. You tell it, keep

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paragraphs under three sentences. Or you instruct

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it, never use passive voice and avoid exclamation

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points. Because specificity is what creates repeatable

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behavior. A machine doesn't understand warmth,

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but it perfectly understands a maximum word count.

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And it's an iterative process. Over the first

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few weeks, you'll catch it making mistakes. You

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correct the output. You tell it to remember that

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specific correction. Over time, that voice principles

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file evolves into a living, incredibly accurate

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record of your actual voice. So that solves the

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robot tone. What about keeping my life organized?

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That requires building out workstations. Think

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of workstations as dedicated subfolders for specific

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domains of your life. I really like comparing

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workstations to the rooms in a physical house.

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You wouldn't keep your kitchen blender sitting

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on your bed. It makes no sense. Similarly, your

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highly confidential mortgage refinancing notes

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absolutely shouldn't bleed into your weekly creative

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writing drafts. That's a brilliant way to conceptualize

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it. You need structural boundaries. And we generally

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see two distinct types of workstations you can

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build within this system. So if one type handles

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broad categories, what does a universal workstation

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look like? Universal workstations cover broad

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functional areas that touch multiple parts of

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your life. An email HQ is the perfect example.

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You send emails for your day job, for your personal

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life, maybe for side hustle clients. The core

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rules of what makes a good email for you, like

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your sign off and formatting, apply everywhere.

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So that lives in a universal folder. And the

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second type, I imagine it's something highly

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siloed. Right. Dedicated workstations. These

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cover one highly specific contained domain. a

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folder strictly for personal finances, a folder

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dedicated to a complex upcoming international

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trip, or a folder locked down for one specific

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client launch. And each one of these individual

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workstations gets its own isolated setup. Yes.

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Each dedicated workstation gets its own local

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CLAW .md file and its own localized memory .md

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file. The structure perfectly mirrors your main

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root folder, but the rules inside only apply

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when you're actively working inside that specific

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space. Let me test the logic here. If I create

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a really fantastic rule for formatting emails

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inside my finance workstation, should I copy

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paste that rule up into my universal email HQ?

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No, never duplicate. You should never repeat

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global rules in multiple places across the system.

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It's a core design principle. Duplicate rules

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waste your token limits, and worse, they cause

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inconsistent AI behavior when the system tries

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to reconcile two slightly different versions

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of the same rule. Write the rule once at the

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highest level. Never duplicate it. Exactly. It

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keeps the entire architecture clean, efficient,

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and predictable. Sponsor's hearing. OK, so we've

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built the house. We furnished the individual

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rooms with workstations. What does actually living

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and working inside this system look like on a

00:12:27.879 --> 00:12:30.840
random Tuesday afternoon? And crucially, how

00:12:30.840 --> 00:12:33.120
do we pay the electric bill? Meaning, how do

00:12:33.120 --> 00:12:35.539
we manage the token costs so we don't go broke

00:12:35.539 --> 00:12:37.379
running this thing? Let's look at some advanced

00:12:37.379 --> 00:12:39.960
daily workflows. When you integrate those external

00:12:39.960 --> 00:12:43.240
connectors, the capability styrockets. The first

00:12:43.240 --> 00:12:45.720
amazing use case is automatic meeting follow

00:12:45.720 --> 00:12:47.740
-ups. Walk me through the actual mechanics of

00:12:47.740 --> 00:12:49.919
that. How does it happen? Imagine your Google

00:12:49.919 --> 00:12:52.669
Calendar is securely connected to Cowork. You

00:12:52.669 --> 00:12:55.429
also use a standard tool that records and transcribes

00:12:55.429 --> 00:12:57.830
your Zoom meetings. You simply open your chat

00:12:57.830 --> 00:13:00.129
and ask Claude to handle the follow -up for your

00:13:00.129 --> 00:13:03.090
2 p .m. meeting. Just one simple natural language

00:13:03.090 --> 00:13:05.169
request. That's it. Claude pings the calendar

00:13:05.169 --> 00:13:08.509
API to see who is in the 2 p .m. slot. It pulls

00:13:08.509 --> 00:13:11.110
the WAW transcript from your local folder. It

00:13:11.110 --> 00:13:13.799
reads the entire conversation. identifies the

00:13:13.799 --> 00:13:16.259
agreed -upon next steps, and figures out who

00:13:16.259 --> 00:13:18.899
is responsible for what. It then dynamically

00:13:18.899 --> 00:13:21.360
routes to your email HQ workstation to grab your

00:13:21.360 --> 00:13:24.240
communication rules. Finally, it drafts a perfectly

00:13:24.240 --> 00:13:26.600
formatted follow -up email using your exact tone,

00:13:27.100 --> 00:13:29.700
all from one single prompt. That is incredible

00:13:29.700 --> 00:13:31.940
leverage. What about applying this to project

00:13:31.940 --> 00:13:34.419
management? The sources mention Notion. Notion

00:13:34.419 --> 00:13:37.350
auto projects are a huge unlock. Let's say you

00:13:37.350 --> 00:13:39.169
tell Claude you're traveling to Boston for a

00:13:39.169 --> 00:13:41.909
tech conference in June. Claude automatically

00:13:41.909 --> 00:13:44.679
connects to your Notion workspace. Because it

00:13:44.679 --> 00:13:47.080
checks your memory file, it already knows exactly

00:13:47.080 --> 00:13:49.379
how you like your travel properties formatted.

00:13:50.080 --> 00:13:52.419
It knows you like a column for confirmation numbers

00:13:52.419 --> 00:13:55.360
and a separate view for daily itineraries. It

00:13:55.360 --> 00:13:59.240
builds the complete customized travel board autonomously.

00:13:59.399 --> 00:14:01.519
It's not just generating text anymore. It's generating

00:14:01.519 --> 00:14:04.000
customized software environments based on my

00:14:04.000 --> 00:14:06.259
historical preferences. Precisely. But if you

00:14:06.259 --> 00:14:08.279
want to see the true power of persistent memory,

00:14:08.600 --> 00:14:10.500
the finance tracking is where it gets really

00:14:10.500 --> 00:14:12.519
wild. Tell me about the finance workstation.

00:14:12.669 --> 00:14:14.470
How is that different from just using a spreadsheet

00:14:14.470 --> 00:14:18.070
macro? Whoa. Beat. Imagine it just silently watching

00:14:18.070 --> 00:14:21.090
a messy folder of bank statements. You literally

00:14:21.090 --> 00:14:23.730
just drop raw PDF statements into the mounted

00:14:23.730 --> 00:14:26.309
folder. It instantly reads them. It categorizes

00:14:26.309 --> 00:14:28.429
an entire year of transactions. It groups your

00:14:28.429 --> 00:14:30.250
software subscriptions, your travel expenses,

00:14:30.389 --> 00:14:32.570
your dining out. Then it generates a clean Excel

00:14:32.570 --> 00:14:35.370
summary. It's doing hours of tedious manual data

00:14:35.370 --> 00:14:39.129
entry in seconds. But AI hallucinates. What happens

00:14:39.129 --> 00:14:42.149
when it inevitably makes a mistake? What if it

00:14:42.149 --> 00:14:45.009
categorizes a business lunch as a personal grocery

00:14:45.009 --> 00:14:46.990
expense? You just correct it once in the chat.

00:14:47.110 --> 00:14:48.870
You say, hey, anything from this specific restaurant

00:14:48.870 --> 00:14:51.490
is a business expense. Remember this category

00:14:51.490 --> 00:14:54.409
rule. It instantly writes that logic to the local

00:14:54.409 --> 00:14:57.389
memory .md file inside the finance workstation.

00:14:57.690 --> 00:14:59.769
It will never make that specific mistake again.

00:15:00.169 --> 00:15:02.870
The system actually learns. Two -sex silence.

00:15:03.830 --> 00:15:07.740
That is genuine compounding leverage. But processing

00:15:07.740 --> 00:15:11.179
dozens of PDFs, reading calendar APIs, managing

00:15:11.179 --> 00:15:13.919
Notion databases, doing all of this continuously

00:15:13.919 --> 00:15:16.600
must cost an absolute fortune in API credits.

00:15:16.980 --> 00:15:18.799
It definitely can if you aren't careful with

00:15:18.799 --> 00:15:20.700
your architecture. You need strict cost control

00:15:20.700 --> 00:15:22.559
measures in place. And the biggest secret to

00:15:22.559 --> 00:15:24.899
keeping the bill low is intelligent model selection.

00:15:25.100 --> 00:15:26.620
Explain how we manage that. Are we restricting

00:15:26.620 --> 00:15:28.919
what it can do? Not restricting, just optimizing.

00:15:29.279 --> 00:15:32.000
You should use Claude 3 .5 Sonnet for 80 % of

00:15:32.000 --> 00:15:34.820
your routine tasks. Sonnet is incredibly capable.

00:15:34.860 --> 00:15:37.580
It's very fast. and it is significantly cheaper

00:15:37.580 --> 00:15:40.340
to run. You save the heavier model, Claude Erpus,

00:15:40.820 --> 00:15:43.539
exclusively for highly complex multi -step reasoning

00:15:43.539 --> 00:15:47.580
tasks. So, Sonnet is for the daily grind. Sorting

00:15:47.580 --> 00:15:50.379
the emails, summarizing the transcripts, Obis

00:15:50.379 --> 00:15:53.350
is for the heavy lifting. like analyzing a complex

00:15:53.350 --> 00:15:56.769
legal contract. Exactly. You don't need a supercomputer

00:15:56.769 --> 00:15:59.529
to draft a calendar invite. And the other cost

00:15:59.529 --> 00:16:01.509
-saving measure brings us back to those text

00:16:01.509 --> 00:16:04.210
files. Keep your route instructions ruthlessly

00:16:04.210 --> 00:16:07.450
short. Let the routing map pull detailed contests

00:16:07.450 --> 00:16:10.090
from deeper subfolders only when it is actually

00:16:10.090 --> 00:16:12.590
needed for the task at hand. Before we wrap up,

00:16:12.870 --> 00:16:14.769
the sources mentioned a specific habit to build.

00:16:15.590 --> 00:16:18.409
What exactly is a session audit before closing

00:16:18.409 --> 00:16:21.299
a chat window? It's a really powerful, simple

00:16:21.299 --> 00:16:23.860
prompt to use at the end of your day. Before

00:16:23.860 --> 00:16:26.059
you hit the close button and wipe that temporary

00:16:26.059 --> 00:16:28.500
context window, you just ask Claude to scan our

00:16:28.500 --> 00:16:30.919
current conversation. You ask it to find anything

00:16:30.919 --> 00:16:33.379
worth saving to the memory files and update them.

00:16:33.580 --> 00:16:35.700
It's a quick debrief to ensure nothing valuable

00:16:35.700 --> 00:16:38.500
gets forgotten. Exactly. It ensures the system

00:16:38.500 --> 00:16:41.000
keeps learning and compounding without you having

00:16:41.000 --> 00:16:43.659
to sit there doing manual data entry or trying

00:16:43.659 --> 00:16:45.659
to remember what you discussed three hours ago.

00:16:45.879 --> 00:16:48.559
This whole conversation really highlights a massive

00:16:48.490 --> 00:16:51.610
shift in how we interact with machines. We're

00:16:51.610 --> 00:16:54.230
looking at a profound paradigm shift. For the

00:16:54.230 --> 00:16:56.110
last two years, everyone has been obsessed with

00:16:56.110 --> 00:16:58.669
finding the perfect combination of words. The

00:16:58.669 --> 00:17:01.250
age of obsessing over individual prompt engineering

00:17:01.250 --> 00:17:04.190
is ending. It really is. The focus on the magic

00:17:04.190 --> 00:17:07.569
prompt was a symptom of temporary AI. We're entering

00:17:07.569 --> 00:17:10.970
a completely new era. The new era is context

00:17:10.970 --> 00:17:13.849
engineering. The ultimate utility of artificial

00:17:13.849 --> 00:17:17.559
intelligence no longer depends on perfectly wording

00:17:17.559 --> 00:17:20.839
a single prompt in an empty chat box. It depends

00:17:20.839 --> 00:17:23.700
entirely on building an organized, logical folder

00:17:23.700 --> 00:17:26.019
infrastructure around the AI. It's about building

00:17:26.019 --> 00:17:28.859
a robust foundation. If the foundation is solid,

00:17:29.140 --> 00:17:31.619
the AI does the heavy lifting effortlessly. Your

00:17:31.619 --> 00:17:34.160
Co -Work OS is essentially a living database

00:17:34.160 --> 00:17:36.660
of your professional life, and it compounds in

00:17:36.660 --> 00:17:39.390
value over time. every single session, every

00:17:39.390 --> 00:17:41.549
single correction, teaches the system a little

00:17:41.549 --> 00:17:43.269
more about how you operate and how you think.

00:17:43.450 --> 00:17:45.230
And that's the most beautiful part of this entire

00:17:45.230 --> 00:17:47.529
framework. You don't need a perfect, massive

00:17:47.529 --> 00:17:49.750
system on day one. In fact, you shouldn't try

00:17:49.750 --> 00:17:51.549
to build one. You just need a working system.

00:17:51.789 --> 00:17:54.630
So here is your call to action for today. Start

00:17:54.630 --> 00:17:57.470
incredibly small. Build just your master root

00:17:57.470 --> 00:18:00.869
folder. Set up your claw .md file. Maybe add

00:18:00.869 --> 00:18:03.609
two simple workstations, perhaps an email HQ

00:18:03.609 --> 00:18:06.230
and a project folder. Get comfortable with how

00:18:06.230 --> 00:18:08.250
the active memory talks to the routing file.

00:18:08.450 --> 00:18:11.349
Yeah, let your real actual daily needs dictate

00:18:11.349 --> 00:18:13.869
the structure. Don't build elaborate workstations

00:18:13.869 --> 00:18:15.410
you don't actually use just because they look

00:18:15.410 --> 00:18:17.750
nice in a folder tree. It all comes back to that

00:18:17.750 --> 00:18:19.910
initial frustration we talked about at the start,

00:18:20.309 --> 00:18:23.170
the amnesiac chatbot. You don't have to live

00:18:23.170 --> 00:18:25.109
with a tool that forgets you every single morning

00:18:25.109 --> 00:18:27.369
anymore. You can build a system that actually

00:18:27.369 --> 00:18:29.539
remembers. Right. You're building a permanent

00:18:29.539 --> 00:18:31.680
partner. But stepping back, it leaves us with

00:18:31.680 --> 00:18:34.980
something much deeper to consider. If this persistent

00:18:34.980 --> 00:18:37.960
compounding system perfectly mimics your writing

00:18:37.960 --> 00:18:41.000
style over time, if it learns your organizational

00:18:41.000 --> 00:18:43.680
habits and begins anticipating your decision

00:18:43.680 --> 00:18:46.480
-making processes, will there come a day where

00:18:46.480 --> 00:18:48.680
you actually forget where your natural workflow

00:18:48.680 --> 00:18:51.660
ends and the AI's structural influence begins?

00:18:52.160 --> 00:18:54.700
Beat. What happens when your artificial coworker

00:18:54.700 --> 00:18:56.940
knows your own habits and preferences better

00:18:56.940 --> 00:18:57.500
than you do?
