WEBVTT

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You know, it strikes me that we collectively

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misunderstand the tool we're holding. We look

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at ChatGPT, and we treat it like a poster. You

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put bread in, you get toast out. It's a transactional,

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single -use interaction. But looking at the research

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we have today, that is fundamentally the wrong

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mental model. Completely wrong. The real power

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isn't in the one -off question. It's in treating

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the AI like a system. Yes. A system that remembers,

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a system that learns, and a system that actually

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organizes your chaotic thoughts into something

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coherent. That's the disconnect right there.

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We treat it like a magic eight ball. Yeah. Shake

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it, get an answer, put it down. But the source

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material we're diving into today, systematize

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your workflow. 15 advanced chat GPT hacks. It

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just flips that script. It does. The core argument

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here is simple. If you find yourself typing the

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same context twice, You have already failed.

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Welcome to the Deep Drive. It is good to have

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you here. Today, we are going to try and move

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past the viral tricks. Please! We aren't doing

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write me a poem about a cat in the style of Shakespeare.

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Well, laughing. No, we are not. We want to get

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into the mechanics of building what the source

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calls a personal workflow engine. We have a roadmap

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today that covers setting up memory, automation,

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project structures, and some truly advanced decision

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-making tools. This is the difference between

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playing with a toy and hiring a chief of staff.

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And honestly, it starts with the thing most of

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us get completely wrong. What's that? Identity.

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Right. The foundation. The source calls this

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teaching chat GPT your writing style. I think

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this resonates because, well, how often do we

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find ourselves typing, make this sound more professional,

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or make this shorter? Stop using the word Dell.

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Every single day, it's prompt drift. You spend

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half your energy fighting the AI's default voice,

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which is usually that overly cheerful corporate

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customer service robot. It is exhausting. But

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is it fixable? Because I feel like I fix it in

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one chat, and then I open a new one, and we are

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back to square one. That's exactly what the source

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addresses. It gives us a specific mechanism to

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fix this permanently. OK. And the key is, don't

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describe your style. Show it. Show, don't tell.

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You don't say, I write casually. You take an

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email. You actually sent. when you're proud of,

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paste it in, and use a very specific prompt to

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lock it in. Let's look at that prompt, because

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phrasing seems important. It is. You say, analyze

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this for tone, style, format, and reading level.

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You let the AI break you down. It effectively

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deconstructs your linguistic DNA. And then, this

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is the kicker, you tell it to store that memory

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for a specific context. Like, remember, this

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is how I write to my team. That specific context

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part seems critical. It's everything. Because

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the way I write a script for this deep dive is

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very different from how I write an email to a

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confused accountant. Precisely. The source emphasizes

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one style per context. You can have a client

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email persona, a Twitter thread persona, and

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a strategic memo persona. All stored. All stored

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in memory. So next time, you just draft an email

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to the team and it pulls the team mask off the

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shelf. No more manual correction. I have to admit,

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I... I still struggle with this. I find myself

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manually correcting the tone in almost every

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session because I haven't taken the five minutes

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to set this up. It feels, I don't know, almost

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lazy on my part not to do it. It's not just you.

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The source mentions that personalization settings

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are the features most people skip. They're hidden

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away. They're hidden in the settings menu, but

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they act as a global baseline. You can go in

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there and set a default about you. your role,

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your experience level, your preference for no

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fluff answers. So you're giving the AI a permanent

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dossier on who you are. Exactly. So you don't

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have to introduce yourself every time you walk

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into the room. So does this mean we stop treating

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it like a generic robot? Yes. It becomes a mirror

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of your specific communication style. It stops

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sounding like an AI and starts sounding like

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you on your best day. That is a compelling thought.

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But to make that work, you need a container,

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right? You can't just have all these different

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personas floating around in a void. Right. This

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brings us to the second pillar of our discussion.

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Structure. Specifically, projects. Projects are

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huge. If you're still using the default chat

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history, you know, that infinite scroll of random

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conversations on the left side of the screen.

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Which is most people. It's most people. You are

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living in a messy house. The source describes

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projects as folders with a brain. Folders with

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a brain. Break that down for me. Think about

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your physical desk. You wouldn't stack your tax

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returns, your creative writing journal, and your

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grocery list in one pile, would you? I mean,

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I might, but I shouldn't. Exactly. Right now,

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most people's chat history is that pile. Projects

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let you create distinct workspaces. Okay. One

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project for client work, one for creative writing,

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one for learning Python. And here's the key.

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Each project has its own custom instructions

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and its own files. And there is a specific setting

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here that the source flags as credible project

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-only memory. Yes. This is the safety lock. By

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default, chat GPT's memory can bleed across conversations.

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You do not want the casual, slang -filled tone

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you used in your creative writing project to

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suddenly show up. In your corporate strategy

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project. That would be a career -limiting move.

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It would be awkward, to say the least. Project

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-only memory isolates the context. It ensures

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that what happens in the project stays in the

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project. Right. It's essential for privacy too,

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especially if you're uploading sensitive client

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docs. It reminds me of the concept of context

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switching in human psychology. It takes energy

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to switch from one task to another. By creating

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these projects, you're effectively offloading

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that cognitive load onto the machine. That's

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the perfect analogy. You're building distinct

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rooms for distinct modes of thinking. That's

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it. And sometimes, you don't even want a room.

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Sometimes you just want a sandbox. The source

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mentions temporary chats for this. Right, the

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incognito mode of AI. Basically. These are chats

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that don't save, don't train the model, and don't

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create memories. Okay, so what's that for? It's

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perfect for when you need to ask a dumb question,

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or test a prompt, or run a sensitive role play,

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and you just want the slate wiped clean immediately

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after. It keeps your main memory banks from getting

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polluted with garbage. Why is the isolation of

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memory so critical here? It's context hygiene.

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You don't want your casual chats leaking into

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professional strategy. You keep the signal to

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noise ratio high. Cleanliness is next to godliness,

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even in code. Right. Now let's move to something

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that I think changes the dynamic of the relationship

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entirely. We're talking about automation. Yeah.

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The shift from passive to active. This is where

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it gets fun. Most of us think of Chat GPT as

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a tool we have to pick up and use, but the source

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points out that you can flip that dynamic. You

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can set up a daily reminder system. Give us an

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example of how that works practically because

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my phone already has reminders. True, but your

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phone just pings you with a label. Chat GPT can

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perform a task. A task. You can tell it. Every

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weekday at 8 a .m. send me three important AI

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updates focused on OpenAI and Google. It creates

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a background task. It runs whether you open the

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app or not. So it pushes the information to me.

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It pings you with the briefing. That is a subtle

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but profound shift. It's no longer waiting for

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input. It is initiating the interaction. It's

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massive. And you can scale this up with what

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the source calls the company knowledge base.

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Right, for teams. If you're on a team plan, you

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can connect your Google Drive, your Notion, your

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calendars. So instead of asking chat GPT to search

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the web, You're asking it, what did we decide

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in last week's marketing meeting? And it's pulling

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the answer from your actual internal doc. From

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your stuff. And there's also this mention of

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apps and connectors using the at symbol. I've

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seen that. Yeah. This is the app layer. You type

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at in the chat and you can call up external tools.

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You can summon Khan Academy for a math explanation

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or a design tool to generate a vector image right

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there in the flow of conversation. So no more

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tap switching. It's orchestration. It's fascinating.

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Imagine scaling this. Waking up to a personalized

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briefing created by an agent that ran through

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your internal docs and the external web while

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you slept. It feels like we are inching closer

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to that sci -fi vision of a digital butler. Ideally

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a butler that doesn't judge my calendar management.

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But yes, that's the dream. So if we look at this

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automation layer, it stops being passive. Right.

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It transitions from a tool you hold to an assistant

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that nudges you. It becomes proactive. I want

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to pause for a moment to consider the implications

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of that. But first, let's take a quick break.

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We are back. We've talked about identity, structure,

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and automation. Now I want to get into the act

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of creation itself. Yes. The source mentions

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advanced creation, specifically dealing with

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how we generate output images, code, mini apps.

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This is for the builders. The first hack here

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is model switching. inside custom GPTs. This

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is a bit technical, but super important. Let's

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break it down. People build these custom assistants,

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maybe a writing coach, GPT, but they built it

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six months ago. It's running on an old brain.

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And the source said you can swap that brain out.

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Exactly. You can go into the settings of an old

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GPT and force it to use the new thinking models

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like 01 for deep reasoning. It's like taking

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a vintage car and dropping a Ferrari engine inside.

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That's it. You keep the interface, but the performance

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skyrockets. Speaking of performance, the image

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generation workflow described here seems much

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faster than the usual method. It's the batch

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images hack. Usually people prompt, make a logo.

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Wait, make it blue. Wait. It's so slow. Yeah,

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it's iterative. The source says do it in parallel?

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Tell it. Create a hero image for a sauce website.

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Also create a dark mode version and a minimalist

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thumbnail version. So you get three variations

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instantly. And you can spot the direction you

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like immediately without waiting for three separate

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failures. That brings us to canvas mode. This

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is something I've seen pop up recently. It seems

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to be more than just a chat window, but less

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than a code editor. Canvas is incredible. It's

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essentially a prototyping environment. If you

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ask ChatGPT to build a to -do list app and you're

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in Canvas mode, it doesn't just write the code

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snippet. It renders a preview. You can click

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the buttons. You can check the boxes. So you

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are building software without writing a line

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of code. You're building interfaces. Calculators,

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planners, simple interactive tools. You describe

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it, it appears. What does Canvas mode actually

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represent for a non -coder? Instant prototyping.

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It turns an abstract idea into a clickable reality

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in seconds. It removes the fear of the blank

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page because you can see the thing working immediately.

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That removal of friction is the theme here, but

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I want to go deeper. Let's do it. The final section

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of our roadmap covers deep thinking. We are moving

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beyond simple tasks to research, strategy, and

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complex decision making. This is where the power

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users live. The source highlights deep research.

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combined with your own data. OK. Now, deep research

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is an agent that goes out, reads dozens of websites,

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and compiles a report. That's great. But the

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magic happens when you tell it to cross -reference

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that web data with your uploaded internal strategy

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documents. So it's validating your internal assumptions

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against the external reality of the market. Precisely.

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It's a reality check machine. And speaking of

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reality checks, there's this decision simulator.

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I love this one. How does that work? You're stuck

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on a big decision. Maybe, should we? pivot to

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enterprise clients. Instead of asking for advice,

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which can be vague, you ask for a simulation.

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A simulation. You say, simulate this decision

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from three perspectives. My customer, a competitor.

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and a skeptical investor. A skeptical investor.

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That's a useful perspective to have on demand.

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It is. And the AI role plays all three. It predicts

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the friction points, the counter moves by the

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competitor, the doubts of the investor. It helps

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you see your blind spots. It's not a crystal

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ball. No, but it clarifies the risk. That is

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powerful. There is also a tool mentioned for

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documentation, the SOP generator. But the method

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described is conversational. This is the interview

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mode hack. Yeah. Most people hate writing standard

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operating procedures, SOPs. It's boring. It's

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so boring. So instead of writing it, you tell

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chat GPT. Ask me clarifying questions one by

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one about how I do this task and then turn my

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answers into a detailed SOP. So it interviews

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you about your own job. Yes. You just brain dump

00:12:32.649 --> 00:12:35.509
the answers verbally or in quick text and it

00:12:35.509 --> 00:12:37.590
structures the chaos into a formal document.

00:12:37.730 --> 00:12:40.169
It captures your tacit knowledge. The stuff you

00:12:40.169 --> 00:12:42.350
do without thinking and writes it down for you.

00:12:42.509 --> 00:12:45.519
And finally, there is the concept of the knowledge

00:12:45.519 --> 00:12:48.500
graph. This feels like a long -term project.

00:12:48.840 --> 00:12:51.059
This is for the lifelong learners. Yeah. You

00:12:51.059 --> 00:12:53.019
create a project called Thinking and Research.

00:12:53.360 --> 00:12:55.559
You dump your book notes, your random ideas,

00:12:55.960 --> 00:12:58.620
your article summaries into it over months. Okay.

00:12:59.240 --> 00:13:01.879
And periodically you ask it, what patterns are

00:13:01.879 --> 00:13:04.440
emerging in my thinking or connect this new idea

00:13:04.440 --> 00:13:07.279
to things I wrote three months ago? It's looking

00:13:07.279 --> 00:13:09.460
for the connective tissue in your own intellect.

00:13:09.679 --> 00:13:12.220
It is. It's finding the threads you forgot you

00:13:12.220 --> 00:13:14.990
were weaving. What is the ultimate value of the

00:13:14.990 --> 00:13:18.190
knowledge graph approach? Synthesis. It finds

00:13:18.190 --> 00:13:20.210
connections between your ideas that you might

00:13:20.210 --> 00:13:22.570
have forgotten. It stops your knowledge from

00:13:22.570 --> 00:13:24.629
being just a pile of notes and turns it into

00:13:24.629 --> 00:13:28.070
a web of understanding. Synthesis. That is the

00:13:28.070 --> 00:13:30.350
goal. We have covered a lot of ground here. We

00:13:30.350 --> 00:13:33.250
have. From establishing an identity to building

00:13:33.250 --> 00:13:36.309
a structure, automating the mundane, prototyping

00:13:36.309 --> 00:13:39.590
ideas, and finally, using the machine to deepen

00:13:39.590 --> 00:13:42.340
our own thinking. It's a lot. And the source

00:13:42.340 --> 00:13:45.120
makes a great point in the big idea recap. The

00:13:45.120 --> 00:13:47.279
people getting the most value aren't the ones

00:13:47.279 --> 00:13:50.659
writing the perfect complex super prompt. No.

00:13:50.799 --> 00:13:52.820
They're the ones building systems. It is a shift

00:13:52.820 --> 00:13:56.580
from chat bot, which is transactional, to operating

00:13:56.580 --> 00:13:58.960
system, which is cumulative. Right. And the advice

00:13:58.960 --> 00:14:02.840
is don't try to do all 15 of these things tomorrow.

00:14:03.039 --> 00:14:05.940
You will burn out. Just pick one. Pick one. Maybe

00:14:05.940 --> 00:14:08.120
just set up the project only memory so your work

00:14:08.120 --> 00:14:11.080
stays clean. Or maybe just try the writing style

00:14:11.080 --> 00:14:13.440
hack so you stop fighting the tone. Stack them

00:14:13.440 --> 00:14:16.799
gradually? Exactly. Lego blocks, not a monolith.

00:14:17.480 --> 00:14:20.000
So here is our challenge to you, the listener.

00:14:20.659 --> 00:14:24.399
Pick one. Try the decision simulator on a choice

00:14:24.399 --> 00:14:27.139
you're avoiding making. Or try the writing style

00:14:27.139 --> 00:14:28.980
hack and see if it feels like looking in a mirror.

00:14:29.500 --> 00:14:32.279
And honestly, try the SOP generator if you hate

00:14:32.279 --> 00:14:35.419
documentation. It's a lifesaver. It really sounds

00:14:35.419 --> 00:14:38.019
like it. You know, as we close, I'm left with

00:14:38.019 --> 00:14:41.299
this thought about memory. We're outsourcing

00:14:41.299 --> 00:14:44.299
not just our tasks, but the retention of our

00:14:44.299 --> 00:14:48.120
context. If the AI remembers our style, our past

00:14:48.120 --> 00:14:49.960
projects, our patterns of thought better than

00:14:49.960 --> 00:14:52.980
we do, it changes how we view our own past work.

00:14:53.279 --> 00:14:55.379
It's no longer something we leave behind. It's

00:14:55.379 --> 00:14:57.639
something that actively informs what we do next.

00:14:57.879 --> 00:14:59.659
It makes everything we've ever done available

00:14:59.659 --> 00:15:03.269
to us right now. That's a superpower. A superpower

00:15:03.269 --> 00:15:05.549
indeed. Thank you for listening to this deep

00:15:05.549 --> 00:15:06.990
dive. Catch you on the next one.
